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iceVectorIdE10HostVectorEv_ZNK7xgboost16HostDeviceVectorIdE11HostCanReadEv_ZNK7xgboost16HostDeviceVectorIdE12HostCanWriteEv_ZNK7xgboost16HostDeviceVectorIdE13DeviceCanReadEv_ZNK7xgboost16HostDeviceVectorIdE14DeviceCanWriteEv_ZNK7xgboost16HostDeviceVectorIdE12DeviceAccessEv_ZNK7xgboost16HostDeviceVectorIdE9SetDeviceENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIdE6ResizeEmd_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEC2EmS3_NS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEC2ESt16initializer_listIS3_ENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEC1ESt16initializer_listIS3_ENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEC2ERKSt6vectorIS3_SaIS3_EENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEC1ERKSt6vectorIS3_SaIS3_EENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEED2Ev_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEC2EOS4__ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEC1EOS4__ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEaSEOS4__ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE4SizeEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE5EmptyEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE6DeviceEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE10DeviceSpanEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE15ConstDeviceSpanEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE10DeviceSpanEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE13DevicePointerEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE18ConstDevicePointerEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE13DevicePointerEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE11HostPointerEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE8HostSpanEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE4FillES3__ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE15ConstHostVectorEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE8HostSpanEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE13ConstHostSpanEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE16ConstHostPointerEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE11HostPointerEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE10HostVectorEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE11HostCanReadEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE12HostCanWriteEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE13DeviceCanReadEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE14DeviceCanWriteEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE12DeviceAccessEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIfEEE9SetDeviceENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEEC2EmS3_NS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEEC1EmS3_NS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEEC2ESt16initializer_listIS3_ENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEEC1ESt16initializer_listIS3_ENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEEC2ERKSt6vectorIS3_SaIS3_EENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEEC1ERKSt6vectorIS3_SaIS3_EENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEED2Ev_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEED1Ev_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEEC2EOS4__ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEEC1EOS4__ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEEaSEOS4__ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE4SizeEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE5EmptyEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE6DeviceEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE10DeviceSpanEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE15ConstDeviceSpanEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE10DeviceSpanEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE13DevicePointerEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE18ConstDevicePointerEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE13DevicePointerEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE10HostVectorEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE11HostPointerEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE8HostSpanEv_ZN7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE4FillES3__ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE15ConstHostVectorEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE8HostSpanEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE13ConstHostSpanEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE16ConstHostPointerEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE11HostPointerEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE10HostVectorEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE11HostCanReadEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE12HostCanWriteEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE13DeviceCanReadEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE14DeviceCanWriteEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE12DeviceAccessEv_ZNK7xgboost16HostDeviceVectorINS_6detail20GradientPairInternalIdEEE9SetDeviceENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIiEC2EmiNS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIiEC1EmiNS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIiEC2ESt16initializer_listIiENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIiEC1ESt16initializer_listIiENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIiEC2ERKSt6vectorIiSaIiEENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIiEC1ERKSt6vectorIiSaIiEENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIiED2Ev_ZN7xgboost16HostDeviceVectorIiED1Ev_ZN7xgboost16HostDeviceVectorIiEC2EOS1__ZN7xgboost16HostDeviceVectorIiEC1EOS1__ZN7xgboost16HostDeviceVectorIiEaSEOS1__ZNK7xgboost16HostDeviceVectorIiE4SizeEv_ZNK7xgboost16HostDeviceVectorIiE5EmptyEv_ZNK7xgboost16HostDeviceVectorIiE6DeviceEv_ZN7xgboost16HostDeviceVectorIiE10DeviceSpanEv_ZNK7xgboost16HostDeviceVectorIiE15ConstDeviceSpanEv_ZNK7xgboost16HostDeviceVectorIiE10DeviceSpanEv_ZN7xgboost16HostDeviceVectorIiE13DevicePointerEv_ZNK7xgboost16HostDeviceVectorIiE18ConstDevicePointerEv_ZNK7xgboost16HostDeviceVectorIiE13DevicePointerEv_ZN7xgboost16HostDeviceVectorIiE10HostVectorEv_ZN7xgboost16HostDeviceVectorIiE11HostPointerEv_ZN7xgboost16HostDeviceVectorIiE8HostSpanEv_ZN7xgboost16HostDeviceVectorIiE4FillEi_ZNK7xgboost16HostDeviceVectorIiE15ConstHostVectorEv_ZNK7xgboost16HostDeviceVectorIiE8HostSpanEv_ZNK7xgboost16HostDeviceVectorIiE13ConstHostSpanEv_ZNK7xgboost16HostDeviceVectorIiE16ConstHostPointerEv_ZNK7xgboost16HostDeviceVectorIiE11HostPointerEv_ZNK7xgboost16HostDeviceVectorIiE10HostVectorEv_ZNK7xgboost16HostDeviceVectorIiE11HostCanReadEv_ZNK7xgboost16HostDeviceVectorIiE12HostCanWriteEv_ZNK7xgboost16HostDeviceVectorIiE13DeviceCanReadEv_ZNK7xgboost16HostDeviceVectorIiE14DeviceCanWriteEv_ZNK7xgboost16HostDeviceVectorIiE12DeviceAccessEv_ZNK7xgboost16HostDeviceVectorIiE9SetDeviceENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIiE6ResizeEmi_ZN7xgboost16HostDeviceVectorIhEC2EmhNS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIhEC1EmhNS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIhEC2ESt16initializer_listIhENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIhEC1ESt16initializer_listIhENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIhEC2ERKSt6vectorIhSaIhEENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIhEC1ERKSt6vectorIhSaIhEENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIhED2Ev_ZN7xgboost16HostDeviceVectorIhED1Ev_ZN7xgboost16HostDeviceVectorIhEC2EOS1__ZN7xgboost16HostDeviceVectorIhEC1EOS1__ZN7xgboost16HostDeviceVectorIhEaSEOS1__ZNK7xgboost16HostDeviceVectorIhE4SizeEv_ZNK7xgboost16HostDeviceVectorIhE5EmptyEv_ZNK7xgboost16HostDeviceVectorIhE6DeviceEv_ZN7xgboost16HostDeviceVectorIhE10DeviceSpanEv_ZNK7xgboost16HostDeviceVectorIhE15ConstDeviceSpanEv_ZNK7xgboost16HostDeviceVectorIhE10DeviceSpanEv_ZN7xgboost16HostDeviceVectorIhE13DevicePointerEv_ZNK7xgboost16HostDeviceVectorIhE18ConstDevicePointerEv_ZNK7xgboost16HostDeviceVectorIhE13DevicePointerEv_ZN7xgboost16HostDeviceVectorIhE10HostVectorEv_ZN7xgboost16HostDeviceVectorIhE11HostPointerEv_ZN7xgboost16HostDeviceVectorIhE8HostSpanEv_ZN7xgboost16HostDeviceVectorIhE4FillEh_ZNK7xgboost16HostDeviceVectorIhE15ConstHostVectorEv_ZNK7xgboost16HostDeviceVectorIhE8HostSpanEv_ZNK7xgboost16HostDeviceVectorIhE13ConstHostSpanEv_ZNK7xgboost16HostDeviceVectorIhE16ConstHostPointerEv_ZNK7xgboost16HostDeviceVectorIhE11HostPointerEv_ZNK7xgboost16HostDeviceVectorIhE10HostVectorEv_ZNK7xgboost16HostDeviceVectorIhE11HostCanReadEv_ZNK7xgboost16HostDeviceVectorIhE12HostCanWriteEv_ZNK7xgboost16HostDeviceVectorIhE13DeviceCanReadEv_ZNK7xgboost16HostDeviceVectorIhE14DeviceCanWriteEv_ZNK7xgboost16HostDeviceVectorIhE12DeviceAccessEv_ZNK7xgboost16HostDeviceVectorIhE9SetDeviceENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIhE6ResizeEmh_ZN7xgboost16HostDeviceVectorIaEC2EmaNS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIaEC2ESt16initializer_listIaENS_9DeviceOrdE_ZN7xgboost16HostDeviceVectorIaEC1ES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L9hwHEdH3%(uHe[A\A]A^A_]wHHtHǔY(HXHHהHXH9uNLpLxLtLpHXLHDžpLxLӔLҔH= /tH)M2'HXHHw֔lIεL3fDAUATUSHXHoHI=ӔA赱Ic1HcHHHH9HHHH9xHH)بt~I4$HH~@ooNoV o^0H|$HHH)D$I|$)L$)T$()\$8t$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HHPH9@M$HI|$HAo AohAop Aox0MH@)d$)l$)t$()|$8LL$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HcM$HHI|$HsHEoEoJEoR EoZ0MZ@D)D$D)L$L\$HD)T$(D)\$8t$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HHPH9HX[]A\A]DH1ZDAUATUSHXHoHIMєAůIc1HcHHHH9HHHH9xHH)بt~I4$HH~@ooNoV o^0H|$HHH)D$I|$)L$)T$()\$8t$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HHPH9@M$HI|$HAo AohAop Aox0MH@)d$)l$)t$()|$8LL$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HsM$HHI|$HsHEoEoJEoR EoZ0MZ@D)D$D)L$L\$HD)T$(D)\$8t$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HHPH9HX[]A\A]DH1ZDUHAWAVAUATSHxH`dH%(HE1HEHhD(MI)LE赭HuLu(L} HcLMIHhLljH}PL]HhHE@ILG LO8ooOoW(DW@ASH}0ATLe8LELEHLMIA4$DU)E)MUnXIZL;ht(HHH;HSH)IIt 1CHEdH3%(uHe[A\A]A^A_]qHHtH”\"H`HH єL`I?uNLpLxLnHpLHDžpHxH`L͔L̔H=/tH,G2!H`HHzДlIѯL3fAUATUSHXHoHI=͔A赫Ic1HcHHHH9HHHH9xHH)بt~I4$HH~@ooNoV o^0H|$HHH)D$I|$)L$)T$()\$8t$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HHPH9@M$HI|$HAo AohAop Aox0MH@)d$)l$)t$()|$8LL$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HM$HHI|$HsHEoEoJEoR EoZ0MZ@D)D$D)L$L\$HD)T$(D)\$8t$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HHPH9HX[]A\A]DH1ZDAUATUSHXHoHIM˔AũIc1HcHHHH9HHHH9xHH)بt~I4$HH~@ooNoV o^0H|$HHH)D$I|$)L$)T$()\$8t$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$H!HPH9@M$HI|$HAo AohAop Aox0MH@)d$)l$)t$()|$8LL$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$HM$HHI|$HsHEoEoJEoR EoZ0MZ@D)D$D)L$L\$HD)T$(D)\$8t$Ht$Ht$Ht$Ht$Ht$Ht$Ht$Ht$H-HPH9HX[]A\A]DH1ZDUHAWAVAUATSHLgdH%(HE1HLLpLM7I/ɔHc觧LHLJ7L9IGHM9HHHHHHHHHHDMGIWMh IHM`(MHMPIX8L0D)Ix@L8EMXI@0L L`M)LEL(HXH@LhHPȦLhLLL HcH(MIAL@HuL8LXH0Ao AoYIA Aoi(IQ8AI@VIAULPHUA2AUMLHE)M)])@mgLhXZML9`t(HIH;HSH)IIt *CIL;LHHL9MLFLLLHLL+L9vHH2fHEdH3%(uHe[A\A]A^A_]-jHHtH HHHɔLI;uNLpLxL&gHpHLHDžpHxLŔLŔH=n/tH?藨]HHH ɔld9f.DUHHAWAVAUATSHHLhHLrdH<%(H}1LLM]ŔMHc HLK >L9IGH M9,LLHHHHIHHHfDLMHMpA@Ma I LMQMi01IQ8L@EIMYIA(L0H`L)IYH@LPMi@LFHXL8LhHH(L0L LLcH8HhL(AIMMM M]8HULAoEAoMAoU(AE@RLhHPLMMHHLXL]AU7H@E)E)MUFdXH ZL;`tFH(E1H HH;HSH)IIt #'ICH M9wIL; iHHLH9IHLFLH+LL LLH9vHHfHEdH3%(uHe[A\A]A^A_]mfHHtHA ,HHHŔLI9uNLpLxLfcLpHLHDžpLx LLH=/tH;פHHHJŔl褤9f.DUHHAWAVAUATSHHL`HLrdH<%(H}1LLM5MHcMHLK >L9IGH M9LLHHHHIHHHfDLMHIHMi I1HMa0MQIQ8IY@L0D.MYLPEIA(MqL(L`M)HXLEH@LhH8pLLLLhL(HcMAI(\L@H8LXII8Ao AoYIA Aoi(Aq@HMIILuHEAVAULPLu7AUH0)M)])@m`LhXZML9`t(HIH;HSH)IIt u#CIL; HHHH9ILFL LLHHH+H9vHH3HEdH3%(uHe[A\A]A^A_]bHHtHHHIA”LI9uNLpLxL_LpHLHDžpLx6 L>L6H= /tLd8?HHIl 9UHHAWAVAUATSHHL`HLrdH<%(H}1LLM=HMHc轜HLK >L9IGH M9 LLHHHHIHHHfDLMHIHMi I1HMa0MQIQ8IY@L0D.MYLPEIA(MqL(L`M)HXLEH@LhH8LLLLhL(HcMAIL@H8LXII8Ao AoYIA Aoi(Aq@HMIIN`LuHEAVAULPLu7AUH0)M)])@m\LhXZML9`t(HIH;HSH)IIt CIL; HHHH9ILFL LLHHH+H9vHH2f.HEdH3%(uHe[A\A]A^A_]=_HHtHHHI詾LI9uNLpLxL6\LpHLHDžpLxL覺L螺H=~/tL4觝mHHIlt9f.DUHHAWAVAUATSHHLpHLzdH<%(H}1LLM診Hc LHLJ ?L9IGH M9HIHHLHHHLHfDLDA@HMQIyHhIZ8I2HMbMj IR0MZHPIB(L`MrL8HXH)Mb@H@HHIGL0H@8L`LHHL0HhIM H(IAMAT$@IN`MLuHHH@Ao$AoL$M\$ AoT$(ID$8LhAVLP6SULH8L]HE)E)MUHYH`LXXZLM9tXH(E1H II@IRI:MHhH)III IAFML9wIL; ?LHLL9MLLFLL+LL LLL9vSHHLIABH IL9,IL; nfDHEdH3%(uHe[A\A]A^A_][HHtH HHI聺LI;uNLpLxLXHpHLHDžpHxvL~LvH=V/tL0E HHIlL9UHHAWAVAUATSHHLpHLzdH<%(H}1LLM舶HcLHLJ ?L9IGH M9HIHHLHHHLHfDLDA@HMQIyHhIZ8I2HMbMj IR0MZHPIB(L`MrL8HXH)Mb@H@HHIGL0H@L`LHHL0HhIM H(IAMPAT$@IMLuHHH@Ao$AoL$M\$ AoT$(ID$8LhAVLP6SULH8L]HE)E)MU)UH`LXXZLM9tYH(E1H IIDIRI:MHhH)III IAFML9wIL; ?LHLL9MLLFLL+LL LLL9vSHHLIABH IL9,IL; nfDHEdH3%(uHe[A\A]A^A_]VHHtHHHIaLI;uNLpLxLSHpHLHDžpHxVL^LVH=6/tL,_%HHIҵl,9U1AHAWIAVL`AUATSHHWdH%(HE1HhLPH~OY^u? HEdH3%(He[A\A]A^A_]ÐHHtHhL`H@MMoIM`@LIHIXD(IxL EIp MH(HMP0MX8LPM)LEHHXH8L@LHL0LXHLHcHMILNH HUH@L0o oYLI oi(LY8A@RLAULH7H8LMIAUL]E)M)]) mQLXXZIL9Pt(HHH;HSH)IIt CIL9YSHHtHHHH@HH>uNLpLxLPLpHLHDžpLx5L=L5H=.tHc)>:HHH豲l 9fDU1AHAWIAVL`AUATSHHWdH%(HE1HhLPH{Y^u?c HEdH3%(He[A\A]A^A_]ÐHH/tHhL`H@MMoIM`@LIHIXD(IxL EIp MH(HMP0MX8LPM)LEHHXH8L@LHL0ٌLXHLHcHMIL.H HUH@L0o oYLI oi(LY8A@RLAULH7H8LMIAUL]E)M)]) mMLXXZIL9Pt(HHH;HSH)IIt CIL9YPHHtHsHHH HH>uNLpLxLMLpHLHDžpLxLLH=.tHC&:HHH葯l뎔9fDU1HAWIAVHhL`AUATSHHWdH%(HE1HHLL@Q=IY^u>BHEdH3%(He[A\A]A^A_]HHݲtHhL`H@MGIGMh@IHM`8IXIpIxL D)MH L0EMP(MX0HLPM)LEHHXL8L@LH踉LXHLHcHMIL H HUIH@L0oo_LW oo(HG8O@R6H8AULHMLLUAUHE)M)]) mJLXXZI8L9Pt(HHH;HSH)IIt CIL9XMHHtHgRHHHLI9uNLpLxLJLpHLHDžpLxLLH=.tH"#:HHHplʋ9DU1AHAWIAVL`AUATSHHWdH%(HE1HhLPHFY^HEdH3%(He[A\A]A^A_]HHHH蛫LI;uNLpLxL(IHpHLHDžpHxL蘧L萧H=p.蝊DIL9w;HHHhL`HMDMwHIZILIJIrHXIz MB(H MJ0HMZ8Mb@A@HPHHH)H@H(IGL0L8L@ᅔHPHHHIL HIH HXMI|$ MD$8L]H8H0Ao$AoL$H}AoT$(EL$@ASLXS0H(LEL@DMLM)E)MUFLPHHXZM2I9]HE1H I6IIQI9MHXH)IIt+I I AFML9wLIAAH 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GLVL9vD7CfIL9D$LCHL$`Lt$XLH+HT$XH9Lt$XH|$PLLGH|$PIHǺXH5R 0H5%HIT0H5ݥLuTLl$PLIUIu`THH5aC @L9rLL)ZL9rHLL)I1AIthItTIt@It,ItIDETHDE\HDETHDE\HDETHDE\HH9 DETD\F\(DTFT(D\F\(DTFT(D\F\(DTFT(D\F\(HH9uI1AtItcItPIt=It*ItID7E7HD7E7HD7E7HD7E7HD7E7HD7E7HH9D7E7D\7F\>DT7FT>D\7F\>DT7FT>D\7F\>DT7FT>D\7F\>HH9u)AoEofAEEo7Do?fEE7>LCH;I)LtLhH{(HS0H)tLSHt$(HL HL$`HHL$XLzfLnLL$0LD~d$ H\$H|$LL$xfElH\$pD)d$`H|$XHtH$dH3%(uaHĨ[]A\A]A^A_AE@7A7%Ht$(HS(LH|$`HEp;VM HH|$PHt(!H HH|$XHt H舝H|$`Huf.fUfHAWAVAUIATMSHHIXHI+HHLdH%(HE1)@HHDžPHHy(t-L@HIL HMLLLtf)`)p)MH5H(HHDžHHHMUpE1HBoD> fEBoL>0Bod>@E$7Do|7Bot>PFoD>`FoT>pfEFt>oT7 fBD> o\70fBL>0o|7@fBd>@ol7PfBt>PDoL7`fEFD>`Do\7pHfEFT>L96HH;LVD7E7I9%D\7GLVL9D\7GLVI9D\7GLVI9D\7GLVI9D\7GLVI9D\7GLVI9D\7GLVI9D\7GLV L9vqD\7 GLV I9s^D\7 GLV L9vKD\7 GLV L9v8D\7 GLV L9v%D\7 GLVL9vD7CfIL9D$LCHL$`Lt$XLH+HT$XH9Lt$XH|$PLL.H|$PHǺXH5"H5HIY;0H5LE;Ll$PLIUIu0;HH5˨1*@sڈL9rLL)ZL9rHLL)I1AIthItTIt@It,ItIDETHDE\HDETHDE\HDETHDE\HH9 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H=n詛wH=b蝛wH=V葛wH=J腛wH$L$H=.H\$0Ld$8_wH$H=H\$0FwH=:wH=.wfDH=wLH|$H|$0H|$(?H|$0\H|$(LOLwH$H$H=vH\$0HL$8觚wH=`蛚wH=T菚wLH+zHC+zI`+zIB+zH*zH+zHe+zH+zL$ILD$0*zI+zI+zI*zf.AWAVAUATUHSH(Hw(HGHHO Lg0LnHD$H_8H $LHt$L9vk@MuIHT$I~@MFPL9t.wI~ MN0L9twI>MVL9<wI`L9t$uIL9l$wH|$H9|$9L;<$tFI@IOPH9tƴwI Iw0H9t贴wI?MoL9蟴wI`L9<$uI9tBH{@L{PL9t~wH{ Ls0L9tlwH;HSH9DWwH`I9uH}HCLeHH](Ml$I9IH;HIwMIAI9Mt}ItfItTItBIt0ItIt H;HгwH;HijwH;H踳wH;H謳wH;H蠳wH;H蔳wH;H舳wI9vPH;H@wwH{nwH{ewH{\wH{SwH{JwH{AwH{8wI9wH}H([]A\A]A^A_w@H`I9{H}HH([]A\A]A^A_I`L9<$@DI`L9t$IL9l$ZDM9QI@M_PL9t膲wI I_0H9ttwI?IGH9tcwI`M9uDI`M9ufIUUUUUUUAWAVAUATIUSHH(LoHHw(dH%(HD$1HW0H+W8HLLC HL+CH)HIHLHHDHIM9LLSMM)LIL)HwMt$IEHk0LULUM<$LT$MMt M.Lt$IRIAHD$ML}0LuB0Ml$(L} Mt$ LLt M Ll$IIELDE0Lm(B/H}PH}@Mt$@Md$HMMt MLd$IIE>D}PLeHB'HkHHEHfHnfHnHfHnflflK0[@HD$dH3%(6H([]A\A]A^A_fM>HD$DM0L+MhbfLqK 6I9oMҾHIEMl2I9J<wLCHLHs(L)IHIPL4H9t H)LwH;芯wL;LkMA~M,.Ls(LkHIfInflCImHk8HHk@Ht$H} 1PxLL$HE HLM0LLŠwLl$H} Ht$1HxHt$HEHHuLL膠wLt$HEHt$H}@1xL\$HE@HL]PLLEwLd$H}@M)IILO4H)L9vL9LwL9H}H)LwH=,gwH=X;~wfwlwH= EwH=9wH|$LIH(IH} I9twH}H9|$t谭wLpwH[HH{蛭wwIwLRxHHbasic_string::_M_construct null not valid/__w/ml-builds/ml-builds/xgboost/src/c_api/c_api.ccSaving into deprecated binary model format, please consider using `json` or `ubj`. Model format is default to UBJSON in XGBoost 2.1 if not specified.Current DMatrix type does not support set data.binary saving only supported by SimpleDMatrix/__w/ml-builds/ml-builds/xgboost/src/c_api/../common/common.hXGBoost version not compiled with GPU support.p_m->Info().num_col_ <= std::numeric_limits::max()/__w/ml-builds/ml-builds/xgboost/include/xgboost/data.hCheck failed: impl_ != nullptr/__w/ml-builds/ml-builds/xgboost/src/c_api/../common/threading_utils.hSaving model in the UBJSON format as default. You can use file extension: `json`, `ubj` or `deprecated` to choose between formats.Unknown field for Booster feature info:DMatrix has not been initialized or has already been disposed.Check failed: iteration_end == 0Only one of the `ntree_limit` or `iteration_range` can be specified.`ntree_limit` is deprecated, use `iteration_range` instead.Invalid input type for inplace predict.The quantile cut hasn't been generated yet. Unless this is a `QuantileDMatrix`, quantile cut is generated during training.n_numeric == n_features - n_categoriesindptr.back() == vals.size() + mins.size() - n_categoriesFeatureMap feature index exceed boundfeatures.size() <= scores.size()scores.size() % features.size() == 0ulfeatures.size() == scores.size()Check failed: ec == std::errc()XGQuantileDMatrixCreateFromCallbackXGDeviceQuantileDMatrixCreateFromCallbackstatic_cast*>(handle) ->get() ->Info() .group_ptr_.size() == 0Uslice does not support group structureCheck failed: type >= 1 && type <= 4Check failed: ArrayInterface<1>{iface}.is_contiguousi_grad.Shape(0) == i_hess.Shape(0)Mismatched shape between the gradient and hessian.i_grad.Shape(1) == i_hess.Shape(1)i_grad.Shape(0) == p_fmat->Info().num_row_Mismatched size between the gradient and training data.gradient and hessian should be on the same device.half type is only supported for CUDA input.Check failed: IsA(jarray)Size of columns should be the same.%02d:%02d:%02d] basic_string::appendOnly %d dimensional array is valid.USE_CUDAUSE_NCCLUSE_RMMUSE_DLOPEN_NCCLDMLC_LOG_STACK_TRACE_DEPTH%zuInvalid pointer argument: c_interface_strCheck failed: mfnameout_lenout_dptrjson_parametersbufCheck failed: p_outkeydtrainout_indptrout_indicesout_dataCheck failed: page.pagen_threads >= 1out_strjsonubjdeprecatedBUILTIN_PREFETCH_PRESENTMM_PREFETCH_PRESENTUSE_OPENMPGCC_VERSIONDEBUGUSE_FEDERATEDXGDMatrixSetInfoFromInterface2.1.0XGDMatrixSetUIntInfofeature_namefeature_typeout_resultXGBoosterSaveModelToBufferUnknown format: `out_featuresdmatsevnamesc_json_configXGBoosterPredictFromDMatrixiteration_beginiteration_endntree_limittrainingstrict_shapeout_dimout_shapeInplacePredictImplCheck failed: p_predtp_predt->Size() >= n_samplesCheck failed: proxyarray_interfacestr.size() >= 3str[0] == '{'fmapftypei < data.size()end <= data.size()XGBoosterFeatureScoreimportance_typefeature_mapfeature_namestree_idxidx < names_.size()out_n_featuresout_scoresCheck failed: ejson_str1.7.0XGDMatrixCreateFromCSR2.0.0XGDMatrixCreateFromCSRExXGDMatrixCreateFromCSCXGDMatrixCreateFromCSCExXGDMatrixCreateFromURIsilentdata_split_modeXGDMatrixCreateFromCallbackcache_prefixnthreadnextresetCheck failed: _refInvalid handle to ref.max_binXGDMatrixSetDenseInfoCheck failed: t.CContiguous()gradhessgrad_is_cuda == hess_is_cudaarray.valid.Capacity() == 0XGBoosterTrainOneIterXGBoosterBoostOneIterfloat32float64bool8int32int8int16int64Unknown data table type.Check failed: consistent%ldfalseUnknown global parameters: { cannot create std::vector larger than max_size()%s: __pos (which is %zu) > this->size() (which is %zu)Stack trace: _Z +basic_string::basic_string [bt] () /__w/ml-builds/ml-builds/xgboost/src/c_api/c_api_utils.hDMatrix/Booster has not been initialized or has already been disposed./__w/ml-builds/ml-builds/xgboost/src/c_api/../data/adapter.hCheck failed: at_first_Cannot reset IteratorAdapter/__w/ml-builds/ml-builds/xgboost/src/c_api/../data/proxy_dmatrix.hSlicing DMatrix is not supported for Proxy DMatrix.Slicing DMatrix columns is not supported for Proxy DMatrix.syclsycl:cpusycl:gpuUnknown device./__w/ml-builds/ml-builds/xgboost/include/xgboost/context.h$<4̝Bit fieldBooleanIntegerUnsigned integerFloating pointComplex floating pointTimedeltaDatetimeObjectStringUnicodeOtherInvalid type code: in `typestr' of input array. Or open an issue./__w/ml-builds/ml-builds/xgboost/src/c_api/../data/array_interface.h Please verify the `__cuda_array_interface__/__array_interface__' of your input data complies to: https://docs.scipy.org/doc/numpy/reference/arrays.interface.htmltl̥쥂 ,Llmap::at vs. /__w/ml-builds/ml-builds/xgboost/src/c_api/../common/io.hcurr_ptr_ <= p_buffer_->length()read can not have position excceed buffer lengthCheck failed: curr_ptr_ + size <= buffer_size_Check failed: pp_mInvalid DMatrix handleCheck failed: p_mProxy DMatrix cannot return data batch.streamstrides%lu<typestr/__w/ml-builds/ml-builds/xgboost/include/xgboost/json.hInvalid cast, from Missing `version' field for array interfaceOnly version <= 3 of `__cuda_array_interface__' and `__array_interface__' are supported.Missing `typestr' field for array interfaceCheck failed: typestr.size() == 3 || typestr.size() == 4`typestr' should be of format .Missing `shape' field for array interfaceMissing `data' field for array interfaceEmpty data passed in.vector::_M_range_check: __n (which is %zu) >= this->size() (which is %zu)Empty data with non-zero shape.maskj_shape.size() == 1type_length == 1strides.size() == 1Memory should be contiguous.basic_string::at: __n (which is %zu) >= this->size() (which is %zu)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.get(strides.at(0)) == type_lengthvector::_M_realloc_insertvector::_M_default_appendchunksize == groupsUnknown prediction type:std::accumulate(shape.cbegin(), shape.cend(), static_cast(1), std::multiplies<>{}) == chunksize * rowslearnergradient_boostergblineargbtree_model_paramnum_parallel_treestoiUnknown booster:/__w/ml-builds/ml-builds/xgboost/src/c_api/../common/json_utils.hInvalid type for: ``, expecting one of the: {`}, got: `Argument `` is required for ``.`, Argument `missing` is required.i < Dj_strides.size() == j_shape.size()stride and shape don't match.Half type is not supported.ptr % alignment == 0Input pointer misalignment.Check failed: mask_it == array.cend() || IsA(mask_it->second)Masked array is not yet supported.get(array).size() == 1Column: /__w/ml-builds/ml-builds/xgboost/include/xgboost/feature_map.hfid == static_cast(names_.size())unknown feature type, use i for indicator and q for quantityfloatcustom_feature_names.size() == n_featuresIncorrect number of feature names.feature_names.size() == n_featuresfeature_types.size() == n_featuresIncorrect number of feature types.feature_map.Size() == n_featuresout_modelsCheck failed: m == 1 || n == 1n_bits == nShape of bit mask doesn't match data shape. XGBoost doesn't support internal broadcasting.4|||||r||||x||f||||з|||||v|d|R|8|1|| |||׸|Ÿ||||}|c|^|L|:|(|||||ι|||||y|g|U|C|1|| |||׺||||||n|\|J|8|&|||| |||տ|ÿ||||{|i|W|=||||||y|g|U|C|1|||P|>|,|||||ҽ||||||||||||]|K|9|'|||||}|k|Y|G|5|#||||||w|j|]|P|C|6|)||||__Cannot find argument '', Possible Arguments: ---------------- : St11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EESt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EEN4dmlc5ErrorEN4dmlc10ParamErrorEN4dmlc9parameter16FieldAccessEntryEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIiEEiEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIiEEiEEN4dmlc9parameter10FieldEntryIiEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIbEEbEEN4dmlc9parameter10FieldEntryIbEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIfEEfEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIfEEfEEN4dmlc9parameter10FieldEntryIfEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIdEEdEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIdEEdEEN4dmlc9parameter10FieldEntryIdEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIlEElEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIlEElEEN4dmlc9parameter10FieldEntryIlEEN4dmlc6StreamEN4dmlc10SeekStreamEN4dmlc7istream5InBufEN4dmlc7istreamEN7xgboost6common19MemoryFixSizeBufferEN7xgboost6common18MemoryBufferStreamEN4dmlc8DataIterIN7xgboost4data15CSRAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_15CSRAdapterBatchEEEN7xgboost4data10CSRAdapterEN4dmlc8DataIterIN7xgboost4data17DenseAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_17DenseAdapterBatchEEEN7xgboost4data12DenseAdapterEN4dmlc8DataIterIN7xgboost4data17ArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_17ArrayAdapterBatchEEEN7xgboost4data12ArrayAdapterEN4dmlc8DataIterIN7xgboost4data20CSRArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_20CSRArrayAdapterBatchEEEN7xgboost4data15CSRArrayAdapterEN4dmlc8DataIterIN7xgboost4data15CSCAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_15CSCAdapterBatchEEEN7xgboost4data10CSCAdapterEN4dmlc8DataIterIN7xgboost4data20CSCArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_20CSCArrayAdapterBatchEEEN7xgboost4data15CSCArrayAdapterEN4dmlc8DataIterIN7xgboost4data21DataTableAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_21DataTableAdapterBatchEEEN7xgboost4data16DataTableAdapterEN4dmlc8DataIterIN7xgboost4data20ColumnarAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_20ColumnarAdapterBatchEEEN7xgboost4data15ColumnarAdapterEN4dmlc8DataIterIN7xgboost4data16FileAdapterBatchEEEN7xgboost4data12DMatrixProxyEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIjEEjEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIjEEjEEN4dmlc9parameter10FieldEntryIjEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryImEEmEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryImEEmEEN4dmlc9parameter10FieldEntryImEEN7xgboost4data15IteratorAdapterIPvFiS2_PFiS2_15XGBoostBatchCSRES2_ES3_EESt15_Sp_counted_ptrIPN7xgboost7DMatrixELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data12DMatrixProxyELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_11EllpackPageEEELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_16GHistIndexMatrixEEELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_13ExtSparsePageEEELN9__gnu_cxx12_Lock_policyE2EE?0C?C/__w/ml-builds/ml-builds/xgboost/src/c_api/coll_c_api.ccCheck failed: !ptr->second.valid()/__w/ml-builds/ml-builds/xgboost/src/c_api/../collective/../data/array_interface.hCheck failed: res != std::future_status::deferred seconds reached for TrackerFree, killing the tracker.XGBoost is not compiled with federated learning support./__w/ml-builds/ml-builds/xgboost/include/xgboost/collective/socket.hname_strargsTracker is already running.Time out dmlc_communicatorXGTrackerCreatefederatedrabitUnknown communicator:timeoutCheck failed: data.Contiguous()/__w/ml-builds/ml-builds/xgboost/src/c_api/../collective/allreduce.h8見X8ȧ`/__w/ml-builds/ml-builds/xgboost/src/c_api/../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/c_api/../collective/allgather.hSt19_Sp_make_shared_tagSt23_Sp_counted_ptr_inplaceIN7xgboost10collective12RabitTrackerESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEFailed to close /__w/ml-builds/ml-builds/xgboost/include/xgboost/collective/sockTimeout waiting for the tracker./src/c_api/coll_eAworker_off < worldsend_seg.size() != 0recv_seg.size() != 0Broadcast AllgatherV failed, current iteration:/__w/ml-builds/ml-builds/xgboost/src/collective/allgather.ccRing AllgatherV failed, current iterataion:Ring allgather failed, current iteration:/__w/ml-builds/ml-builds/xgboost/src/collective/comm.hCheck failed: sock_.get()Check failed: loop_/__w/ml-builds/ml-builds/xgboost/src/collective/allgather.h*offset.cbegin() == 0vector::_M_range_insert/__w/ml-builds/ml-builds/xgboost/src/collective/allreduce.ccdata.size_bytes() % n_bytes_elem == 0/__w/ml-builds/ml-builds/xgboost/src/collective/../data/array_interface.hRing allreduce small failed.first.size() == data.size()Ring Allreduce failed.Ring scatter reduce failed, current iteration:seg.size() == recv_seg.size()seg_nbytes % sizeof(T) == 0L4<|L<|/__w/ml-builds/ml-builds/xgboost/src/collective/broadcast.ccmask != 0peer != rootbroadcast failedlhs.size() == out.size()Invalid input for reduction./__w/ml-builds/ml-builds/xgboost/src/collective/coll.ccNCCL is required for device communication.xōHƍƍ@ǍčPōʍˍˍ̍ɍʍXύύXЍЍH΍΍Ս֍׍׍ ӍxԍPߍߍߍߍߍ@Xxލ8ߍHXhP(H80`p0@P0p*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIfEEDaSB_EUlSB_SC_E_fEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIfEEDaSB_EUlSB_SC_E0_fEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt4plusIvEfEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIdEEDaSB_EUlSB_SC_E_dEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIdEEDaSB_EUlSB_SC_E0_dEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt4plusIvEdEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIeEEDaSB_EUlSB_SC_E_eEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIeEEDaSB_EUlSB_SC_E0_eEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt4plusIvEeEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIaEEDaSB_EUlSB_SC_E_aEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIaEEDaSB_EUlSB_SC_E0_aEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt4plusIvEaEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt7bit_andIvEaEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt6bit_orIvEaEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt7bit_xorIvEaEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIsEEDaSB_EUlSB_SC_E_sEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIsEEDaSB_EUlSB_SC_E0_sEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt4plusIvEsEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt7bit_andIvEsEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt6bit_orIvEsEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt7bit_xorIvEsEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_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point is not supported for bit wise collective operatioUnknown algorithm for allgather-/__w/ml-builds/ml-builds/xgboost/src/collective/../common/common.hXGBoost version not compiled with NCCL support.Failed to receive error signal./__w/ml-builds/ml-builds/xgboost/src/collective/protocol.h/__w/ml-builds/ml-builds/xgboost/src/collective/comm.ccAnother worker is running into error.Check failed: !info.host.empty()Failed to set timeout on recv.Failed to connect to the error socket.Failed to send shutdown signalThe communicator is being destroyed without a call to shutdown first. This can lead to undefined behaviour.Bootstrap failed to connect to ring next.Failed to get host names from peers.Failed to get the port from peers.peers[comm.Rank()].port == lportFailed to receive the rank for the next worker.Failed to connect to other workers.Check failed: this->channels_.empty()Rank Task got rank sendFailed to verify.Invalid verification number. connected to the trackerinet_ntopGot an invalid host name.p.port != -1socketFailed to send rank.Failed to recv rank.Check failed: workers[r]Bootstrap failed.Failed to listen.Failed to set TCP no delay.Failed to set TCP keeaplive.Failed to close the socket.recv): Failed to call ``: getsockopt(this->Handle(), SOL_SOCKET, SO_DOMAIN, reinterpret_cast(&domain), &len)Unknown IA family.bind failed.getsockname failed.Failed to accept.Invalid world size.St23enable_shared_from_thisIN7xgboost10collective4CommEEN7xgboost10collective4CommEN7xgboost10collective8HostCommEN7xgboost10collective9RabitCommEN7xgboost10collective7ChannelE*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7xgboost10collective9RabitComm9BootstrapENSt6chrono8durationIlSt5ratioILl1ELl1EEEEiNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEUlvE3_EEEEEESt15_Sp_counted_ptrIPN7xgboost10collective9TCPSocketELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost10collective4LoopELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost10collective9TCPSocketESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost10collective7ChannelESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEFailed to get soFailed to set socket to non-blocFailed to set tiFailed to listenFailed to send shutdown command Failed to send print command froFailed to send init command fromFailed to connect to the tracker/src/collective/Failed to send error command froFailed to recv iFailed to bootstrap the communic/__w/ml-builds/ml-builds/xgboost/src/collective/comm_group.cc/__w/ml-builds/ml-builds/xgboost/src/collective/comm_group.hCheck failed: ctx->IsCUDA()Duplicated parameter:Check failed: comm_Invalid communicator type/__w/ml-builds/ml-builds/xgboost/src/collective/../common/json_utils.hSt15_Sp_counted_ptrIPN7xgboost10collective4CollELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost10collective4CommELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost10collective9RabitCommELN9__gnu_cxx12_Lock_policyE2EEdmlc_tracker_uridmlc_tracker_por/__w/ml-builds/ml-builds/xgboost/src/collective/in_memory_handler.ccCheck failed: world_size_ < world_sizeIn memory handler already initialized.In memory handler already shutdown.Check failed: world_size_ > 0jDj$jtjdjTjDj$jdjTjDj$jInvalid reduce operationInvalid data typeFloating point types do not support bitwise operations.pln(q8vy{j: handling requestbasic_string::replace: all requests received: waiting for all clients: sending reply: all replies sent: waiting for current sequence numberin_memory_handle/__w/ml-builds/ml-builds/xgboost/src/collective/loop.ccthis->Block().OK() == this->rc_.OK()Check failed: op.code == Op::kSleepCheck failed: op.sock->NonBlocking()Encountered EOF. The other end is likely closed.Check failed: qcopy.empty() || stop_Exception inside the event loop:Unknown exception inside the event loop.std::future_error: code:Check failed: !qcopy.empty()op.off <= op.nop.n != 0vector::reservePoll timeout: seconds.Poll failed, nfds:/__w/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/socket.hcannot create std::deque larger than max_size()NSt13__future_base13_State_baseV2ENSt13__future_base7_ResultIvEENSt13__future_base13_State_baseV27_SetterIvvEE*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7xgboost10collective4LoopC4ENSt6chrono8durationIlSt5ratioILl1ELl1EEEEEUlvE_EEEEEESt23_Sp_counted_ptr_inplaceINSt13__future_base13_State_baseV2ESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseIvESaIS1_ELN9__gnu_cxx12_Lock_policyE2EEFailed to retrieve socket error.Poll error condiInvalid polling Poll hung up on Worker has stoppInvalid socket o/__w/ml-builds/ml-builds/xgboost/src/collective/result.cc]: - system error:/__w/ml-builds/ml-builds/xgboost/src/collective/socket.ccCheck failed: !this->IsClosed()str.size() < std::numeric_limits::max()static_cast(conn.Domain()) == static_cast(addr.Domain())): Failed to connect to: Error:Failed to get addr info for: , error: 127.0.0.10.0.0.0::1::Retrying connection to for the time.Failed to connect to Failed to get hoFailed to recv sFailed to start tracker, timeout:/__w/ml-builds/ml-builds/xgboost/src/collective/tracker.ccInvalid initialization sequence.Failed to initialize worker proxy.Failed to shutdown socket.Recieved error from [Failed to send error signalFailed to inform worker: for error.rankdmlc_tracker_uridmlc_tracker_portcmdInvalid port.error_portsortbyTrackerpending.size() <= n_workersn_shutdown <= n_workersFailed to get address info:127.Failed to create socket.10.255.255.255Failed to find IP address.Failed to get sock name.Failed to close socket.Failed to bind socket.getsocknameFailed to accept connection.Failed to handle abort.pending.size() < n_workersCheck failed: !runningpending.size() == n_workersn_shutdown >= 0n_shutdown < n_workersInvalid command received.Failed to get socket flag.Failed to set socket to non-blocking.Poll error condition:Invalid polling request.Poll hung up on the other end.world_sizeFailed to send init command from tracker.Connect protocol failed.task_idmsgInvalid print command.Invalid error command.NSt13__future_base21_Async_state_commonV2EN7xgboost10collective7TrackerEN7xgboost10collective12RabitTrackerE*NSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost10collective12RabitTracker3RunEvEUlvE0_EEEENS5_6ResultEEE*NSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost10collective12RabitTracker3RunEvEUlvE0_EEEENS5_6ResultEEE*ZN7xgboost10collective14GetHostAddressEPNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEUlPP8addrinfoE_*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7xgboost10collective12RabitTracker9BootstrapEPSt6vectorINS5_11WorkerProxyESaIS7_EEEUlvE_EEEEEE*St23_Sp_counted_ptr_inplaceINSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost10collective12RabitTracker3RunEvEUlvE0_EEEENS6_6ResultEEESaISC_ELN9__gnu_cxx12_Lock_policyE2EE*NSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIN7xgboost10collective6ResultEEENS_12_Result_base8_DeleterEENSt6thread8_InvokerISt5tupleIJZNS4_12RabitTracker3RunEvEUlvE0_EEEES5_EE*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZNSt13__future_base17_Async_state_implINS1_IS2_IJZN7xgboost10collective12RabitTracker3RunEvEUlvE0_EEEENS6_6ResultEEC4EOSA_EUlvE_EEEEEENSt13__future_base7_ResultIN7xgboost10collective6ResultEEE@je _vH@0ļ4&k7y؅W4Ngm=`X@xPMJ- yCx(,*42q0/'|!1錠9Y>R$n`F"x|+MraB ydiWC*fJ\)c7]`xxֲK}Yq\Ck 3TgffffffQ~jt*Ǻ"<8b->Nc{-1+x#c^- Knu7X%Y^_GzK`eq]p J&gչ o"4%QttS`؈$C(ӦfHRl ۩#j+vv=IJ+10Q=ѬVZbu)j}և]:1VӾa'miK$!Q㢢P@9j>`KUq݉ [qB1h?(SuYQ!"GMk9X 3D۸N <C.{$~ۃ6/l##ՂF!00010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899/__w/ml-builds/ml-builds/xgboost/src/common/../data/../common/io.h/__w/ml-builds/ml-builds/xgboost/src/common/column_matrix.ccgmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_valw_n_bytes == n_bytesw_n_bytes == remainingbad_malloc: Failed to allocate /__w/ml-builds/ml-builds/xgboost/src/common/../data/../common/ref_resource_view.h bytes.mem_->Size() >= nreinterpret_cast(ptr) % std::alignment_of_v == 0N7xgboost6common14MallocResourceESt23_Sp_counted_ptr_inplaceIN7xgboost6common14MallocResourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE?\\\"\b\f\n\r\t\u%04xYou have manually specified the `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.The tree method `gpu_hist` is deprecated since 2.0.0. To use GPU training, set the `device` parameter to CUDA instead. E.g. tree_method = "hist", device = "cuda" Falling back to prediction using DMatrix due to mismatched devices. This might lead to higher memory usage and slower performance. XGBoost is running on: , while the input data is on: Potential solutions: - Use a data structure that matches the device ordinal in the booster. - Set the device for booster before call to inplace_predict. This warning will only be shown once. Empty dataset at worker: ` is deprecated since, use `` instead.device E.g. device=cpu/cuda/cuda:0/src/common/erro/__w/ml-builds/ml-builds/xgboost/src/common/threading_utils.h/__w/ml-builds/ml-builds/xgboost/src/common/quantile.hentries_per_columns.size() == static_cast(n_columns)column_sizes_tloc[i].size() == static_cast(n_columns)entries_per_column.size() == info.num_col_Check failed: nlevel <= std::max(static_cast(1), static_cast(limit_size * eps))vector::_M_fill_insertSortedSketchContainerinvalid init parameter/__w/ml-builds/ml-builds/xgboost/src/common/hist_util.ccCheck failed: !offsetsrow_indices.Size() != 0Check failed: offsets/__w/ml-builds/ml-builds/xgboost/src/common/hist_util.hUnreachableSt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_10SparsePageEEELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_13SortedCSCPageEEELN9__gnu_cxx12_Lock_policyE2EE)A@/__w/ml-builds/ml-builds/xgboost/src/common/host_device_vector.ccSize() == other.Size()Size() == other.size()basic_string::substrCheck failed: outFaled to call munmap: close(handle_->fd) != -1Faled to close: pointer_ <= buffer_.size()file://Only local file is supported.Opening fd >= 0Failed to open:ptr != ((void *) -1)Failed to map: /__w/ml-builds/ml-builds/xgboost/src/common/io.ccmunmap(handle_->base_ptr, handle_->base_size) != -1Check failed: (parsed.protocol == "file://" || parsed.protocol.length() == 0)/__w/ml-builds/ml-builds/xgboost/src/common/io.hNot implementedN7xgboost6common16PeekableInStreamEN7xgboost6common15FixedSizeStreamEN7xgboost6common15ResourceHandlerEN7xgboost6common12MmapResourceEN7xgboost6common25AlignedResourceReadStreamEN7xgboost6common22PrivateMmapConstStreamEN7xgboost6common18AlignedWriteStreamEN7xgboost6common22AlignedFileWriteStreamEN7xgboost6common21AlignedMemWriteStreamE/__w/ml-builds/ml-builds/xgboost/src/common/json.cc can not be indexed by Integer. can not be indexed by string./__w/ml-builds/ml-builds/xgboost/include/xgboost/string_view.hHigh precision number is not supported.Check failed: ret.ec == std::errc()` is not supported for typed array.NumberI32ArrayI64ArrayObject of type , around character position: , "beg <= size_\0 Expecting digitUnknown constructch != -1cursor_.Pos(): raw_str_.size():x PxH`.-----------------S.---#.--z-9x<90;9p;;99<9999999:h<9999P9<99999999<9999999<999999999999990=/__w/ml-builds/ml-builds/xgboost/include/xgboost/json_io.hOnly UBJSON format can handle f64 array.", got: "EOF"\0"N7xgboost5ValueEN7xgboost10JsonStringEN7xgboost9JsonArrayEN7xgboost10JsonObjectEN7xgboost10JsonNumberEN7xgboost11JsonIntegerEN7xgboost8JsonNullEN7xgboost11JsonBooleanEN7xgboost10JsonReaderEN7xgboost10JsonWriterEN7xgboost9UBJReaderEN7xgboost9UBJWriterEN7xgboost14JsonTypedArrayIfLNS_5Value9ValueKindE7EEEN7xgboost14JsonTypedArrayIdLNS_5Value9ValueKindE8EEEN7xgboost14JsonTypedArrayIhLNS_5Value9ValueKindE9EEEN7xgboost14JsonTypedArrayIiLNS_5Value9ValueKindE10EEEN7xgboost14JsonTypedArrayIlLNS_5Value9ValueKindE11EEEUnknown construcExpecting null v/__w/ml-builds/ml-builds/xgboost/src/common/common.h optional, default=, requiredvalue for Parameter exceed bound [ should be greater equal to should be smaller equal to Required parameter is not presentedInvalid Parameter format for expect but value='/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h*p == ')'Invalid NAN literalOut of range valuepos <= value.length()Out of range value for , value='No conversion could be performed/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.hSome trailing characters could not be parsed: 'key has already been registered in Y@v? L APesudoHuberParamThe delta term in Pseudo-Huber lmax_cat + 1 >= n_categoriesPushColPagesketch->temp.size <= max_size, stemp.size=/__w/ml-builds/ml-builds/xgboost/src/common/quantile.cc/__w/ml-builds/ml-builds/xgboost/src/common/categorical.hInvalid categorical value detected. Categorical value should be non-negative, less than total number of categories in training data and less than Maximum cateogry should not be lesser than the total number of categories.hessian.size() == info.num_row_group_ptr.back() == hessian.size()weights.size() == info.num_row_Finalize: invalid maximum size, max_size= 옗Ԙ4$LtĚtdL4$44\<$ ܵĵ|ĶĶķtdTD4$ t\D,캗̺ܼļt\ԿԿ|dT<ddd—D—,———4ٗ4ٗڗڗ|ڗ_ڗFڗ,ڗڗٗٗٗ/__w/ml-builds/ml-builds/xgboost/src/common/../data/adapter.hH Ltemp.size < max_size, stemp.sizeINFO: rmax=, sum_total=, naxt_goal=, size=invalid maximum size max_size=group_ptr.size() >= 2group_ptr.back() == n_samplesinfo.weights_.Size() == n_groupsSize of weight must equal to the number of query groups when ranking group is used.Invalid query group structure. The number of rows obtained from group doesn't equal to the number of rows from the data.src.size == 0this->size == 0mingap=, maxgap=, wgap=bug in combineCheck failed: size <= sa.size + sb.size check quantile stats, nbig=, n= srcsize=, maxsize=, range=, chunk=] rmin=, rmax=, wmin=, v=Check failed: nbig < nquantile: too many large chunkH%H%x%&%%%8%%%%8%Check failed: a.dataCheck failed: a.data && reduced[fidx].dataCheck failed: worker_feature.data()count <= total_entriesh_weights.size() == batch.Size()Invalid size of sample weight.Check failed: !this->columns_size_.empty()PushRowPagen_threads_ >= 1sketches_.size() == n_columns p`P x ` P 8  @"@"`#""P#@#" ##0#"0"0"0$$#####p#P#H$??X?@?(??@PPTR4RRQQQQ|QdQ= 1Failed to get sketch.AllReducen_columns == sketches_.size()num_cuts.size() == 0Number of columns differs across workersMakeCutsp_cuts->cut_values_.HostVector().size() <= std::numeric_limits::max()cut_size > p_cuts->cut_ptrs_.HostVector().back()SketchContainerImplcolumns_size_.size() != 0..000 00/h-/./h-h-h-/x/`/@/(//....11H33p333X1333X1X1X132222p2X28221PGGFFF`EGH\HDH,HHGH Y YZZZZqZVZ8ZZYYP[P[\\\k\Q\6\\[[[Check failed: reduced[i].dataKo;o:_AHostSketchContai>/__w/ml-builds/ml-builds/xgboost/src/common/../common/json_utils.hN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIN7xgboost6common15ParamFloatArrayEEES5_EEN4dmlc9parameter10FieldEntryIN7xgboost6common15ParamFloatArrayEEEQuantileLossParaList of quantiles for quantile l/__w/ml-builds/ml-builds/xgboost/src/common/algorithm.hCheck failed: ctx->IsCPU()/__w/ml-builds/ml-builds/xgboost/src/common/random.harray.size() == weights.size()/__w/ml-builds/ml-builds/xgboost/src/common/../collective/../data/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/common/random.ccfeatures.size() > 0Check failed: ctx_mn8nnmSt23_Sp_counted_ptr_inplaceIN7xgboost16HostDeviceVectorIjEESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE75//__w/ml-builds/ml-builds/xgboost/src/common/ranking_utils.h can only be used with binary labels.Check failed: label_is_integerWhen using relevance degree as target, label must be either 0 or positive integer.Relevance degress must be lesser than or equal to when the exponential NDCG gain function is used. Set `ndcg_exp_gain` to false to use custom DCG gain./__w/ml-builds/ml-builds/xgboost/src/common/ranking_utils.ccg_rank.size() == sorted_idx.size()%u[-]?Check failed: is_binaryCheck failed: label_is_validrank.size() == predt.size()enum_back_map_.count(value) != 0UValue not found in enum declaredInvalid Input: '', valid values are: Enum exisit!) Enums: ), long (non-negative)booleandoubleT%%%d&|% ਠاN4dmlc9parameter10FieldEntryIN7xgboost3ltr10PairMethodEEElambdarank_pair_Method for constlambdarank_num_pNumber of pairs for each sample lambdarank_unbiaUnbiased lambda mart. Use extended IPW to debiaslambdarank_normaWhether to normalize the leaf value for lambda rlambdarank_bias_Lp regularization for unbiased lWhen set to true, the label gain is 2^rel - 1, otherwise it's reKHgY?@חA$@/__w/ml-builds/ml-builds/xgboost/src/common/stats.cct_v.Shape(1) != 0/__w/ml-builds/ml-builds/xgboost/src/common/stats.hCheck failed: alpha >= 0 && alpha <= 1k >= 0ʡhؙ?/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./parameter.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././strtonum.hN4dmlc9parameter10FieldEntryIN7xgboost6common27ProbabilityDistributionTypeEEEaft_loss_distribChoice of distribution for the noise term in Accelerated FailureScaling factor used to scale the distribution in Accelerated FaiInvalid thread limit for OpenMP./__w/ml-builds/ml-builds/xgboost/src/common/threading_utils.cclimit >= 1Invalid cgroupv2 file./sys/fs/cgroup/cpu/cpu.cfs_quotapu/cpu.cfs_perioTimer for calls @ us======== Monitor ( ======== did not get stopped properly..A/src/common/time/__w/ml-builds/ml-builds/xgboost/src/common/version.ccfi->Read(&read[0], verstr.size()) == verstr.size()Check failed: fi->Read(&major)Check failed: fi->Read(&minor)Check failed: fi->Read(&patch)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 agaibad optional access/__w/ml-builds/ml-builds/xgboost/src/context.ccBoth `device` and `gpu_id` are specified. Use `device` instead.Check failed: opt_id.has_value()Invalid value for `gpu_id`. Got:Invalid argument for `device`. Expected to be one of the following: - cpu - cuda - cuda: # e.g. cuda:0 - gpu - gpu: # e.g. gpu:0 gpu(:[0-9]+)?|cuda(:[0-9]+)?|cpu|sycl(:cpu|:gpu)?(:-1|:[0-9]+)?sycl(:cpu|:gpu)?(:-1|:[0-9]+)?opt_id.value() <= std::numeric_limits::max()XGBoost is not compiled with CUDA support.new_d.ordinal == this->device_.ordinalthis->device_.ordinal == DeviceOrd::CPUOrdinal()this->device_.ordinal > DeviceOrd::CPUOrdinal()[Internal Error] Unknown parameters passed to the Context {Unexpected end of regex when escaping.Unexpected end of regex when reading control code.Unexpected end of regex when ascii character.Got: `ContextOrdinal value too large.NULSOHSTXETXEOTENQACKalertbackspacenewlinevertical-tabform-feedcarriage-returnSOSIDLEDC1DC2DC3DC4NAKSYNETBCANEMSUBESCIS4IS3IS2IS1exclamation-markquotation-marknumber-signdollar-signpercent-signampersandapostropheleft-parenthesisright-parenthesisasteriskplus-signcommahyphenperiodzeroonetwothreefourfivesixsevenninesemicolonless-than-signequals-signgreater-than-signquestion-markcommercial-atJSVWYleft-square-bracketbackslashright-square-bracketcircumflexunderscoregrave-accentzleft-curly-bracketvertical-lineright-curly-brackettildeDELalnumblankcntrlgraphlowerprintpunctupperxdigit has not been registered in Alias seedlongrandom_stateseed_per_iterationDevice ordinal.Number of threads to use.n_jobsfail_on_invalid_gpu_idvalidate_parametersRandom number seed during training.Seed PRNG determnisticly via iterator number.Fail with error when gpu_id is invalid.Enable checking whether parameters are used or not.Unexpected escape character.Unexpected end of regex when in an open parenthesis.Invalid special open parenthesis.Unexpected end of regex when in brace expression.Unexpected character in brace expression.Unexpected end of character class.Unexpected end of regex when in bracket expression.Unexpected character class open bracket.^$\.*+?()[]{}|.[\()*+?{|^$.[\*^$.[\()*+?{|^$ .[\*^$ Number of NFA states exceeds limit. Please use shorter regex string, or use smaller brace expression, or make _GLIBCXX_REGEX_STATE_LIMIT larger.Unexpected back-reference in polynomial mode.Back-reference index exceeds current sub-expression count.Back-reference referred to an opened sub-expression.XxxxxXzxzz@{{h{Xx{xx |d{{{zzty4yyx$xwPГ蓤@0XInvalid range in bracket expression.Nothing to repeat before a quantifier.Unexpected token in brace expression.Unexpected end of brace expression.Invalid range in brace expression.Invalid collate element.Invalid equivalence class.Invalid character class.Unexpected dash in bracket expression. For POSIX syntax, a dash is not treated literally only when it is at beginning or end.Character is expected after a dash.Unexpected character in bracket expression.Parenthesis is not closed.St19bad_optional_accessN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEES8_EEN4dmlc9parameter10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEESt23_Sp_counted_ptr_inplaceINSt8__detail4_NFAINSt7__cxx1112regex_traitsIcEEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1ELb1EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1EEEww""//\\abf n r /__w/ml-builds/ml-builds/xgboost/src/data/adapter.hCheck failed: columns_ == data::kAdapterUnknownSize || columns_ == batch.columnsNumber of columns between batches changed from /__w/ml-builds/ml-builds/xgboost/src/data/../common/common.hbad any_castauto/__w/ml-builds/ml-builds/xgboost/src/data/data.ccInvalid device ordinal. Data is associated with a different device ordinal than the booster. The device ordinal of the data is: ; the device ordinal of the Booster is: Unknown data type for getting meta info./__w/ml-builds/ml-builds/xgboost/src/data/../collective/../data/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/data/../common/threading_utils.hself_offset.size() == other_offset.size()cache_file.find('#') == std::string::nposOnly one `#` is allowed in file path for cache file specification.Check failed: data_split_mode != DataSplitMode::kColColumn-wise data split is not supported for external memory.this->base_margin_.Size() % this->num_row_ == 0Incorrect size of base margin vector. must be equal to number of columns.group_ptr_.size() == weights_.Size() + 1the actual number of rows given by data.Size of weights must equal to number of rows.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_weights.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_ == 0Size of base margin must be a multiple of number of rows.All feature_types must be one of {int, float, i, q, c}.Meta info like label or weight can not have missing value.Check failed: t_out.CContiguous()Check failed: strm->Read(&name)Check failed: strm->Read(&type_val)Check failed: type == expected_typeCheck failed: strm->Read(&is_scalar)Check failed: strm->Read(field)Check failed: strm->Read(&shape.first)Check failed: strm->Read(&shape.second)Number of columns is expected to be 1.this->num_col_ == that.num_col_Number of columns must be consistent across batches.transpose.offset.Size() == num_columns + 1Check failed: this->base_margin_.Size() % this->num_row_ == 0Incorrect size for base margin.this->labels.Size() % this->num_row_ == 0Label contains NaN, infinity or a value too large.`qid` must be sorted in non-decreasing order along with data.Weights must be positive values.Feature weight must be greater than 0.Check failed: strm->Read(&(shape[i]))Check failed: strm->Read(&field)Binary DMatrix generated by XGBoost: Please process and save your data in current version: Check failed: fi->Read(&num_field)MetaInfo: insufficient number of fields (expected at least fields, but the binary file only contains MetaInfo: the given binary file contains extra fields which will be ignored.ޱޱ`@ ߱߱߱``P0pX xPX000PP0pp00 x@`P@0 x`@0``(8p` @P x`H0PP @@ xX0base_marginlabel_lower_boundlabel_upper_boundfeature_weightsUnknown float field name: group_ptrUnknown uint32 field name: self_data.size(): other_data.size(): beg <= data.size()ptr < offset.size() matrix with entries loaded from result.size() == n_columnsLength of Unknown feature info: group_ptr_.back() == num_row_weights_.Size() == num_row_labels.Shape(0) == num_row_field_cnt == kNumFieldWrong number of fieldsMetaInfo: Invalid format for name == expected_name Expected field: , got: Expected field of type: got field type: Check failed: is_scalarExpected field to be a scalar; got a vectorCheck failed: !is_scalar to be a vector; got a scalarshape.second == 1that.group_ptr_.size() != 0Incorrect size for labels.qidCheck failed: non_decUnknown key for MetaInfo: size == this->num_col_Check failed: infoUnknown feature info name: to be a tensor; got a scalar is no longer supported. again.major >= 1minor >= 6MetaInfo: invalid formatnum_field >= expectedfields.)labels_lower_bound/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.hCheck failed: page_Check failed: valid_query_group/__w/ml-builds/ml-builds/xgboost/src/data/validation.hInvalid group structure./__w/ml-builds/ml-builds/xgboost/src/data/../collective/../data/array_interface.h/__w/ml-builds/ml-builds/xgboost/src/data/../data/adapter.h |d44Check failed: lock_.try_lock()Multiple threads attempting to use Sparse DMatrix. $ 4 L d /__w/ml-builds/ml-builds/xgboost/include/xgboost/linalg.hthis->Data()->Size() == detail::CalcSize(this->shape_)Inconsistent size after modification.shape[i] == r.Shape(i)x""!0"X"d#t#"#D#P$`$#$0$PϮϮЮ@ҮӮԮP֮׮ٮۮXˮPͮPx@ x@--/@0`12346p8*+][XX.RDRkey >= builder_base_row_offsetP1P1h222223 3@3`33@@DCDC8CH=CC`CH=??`BBABBP>AhABP>X>X>A@@@x@P@0@@PAA``@edecc^ dPdc^p`p`cbb`c@c _b(bPc _0_0_aaa`a8aa``b8biijjjjk!kwritten/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_writer.hUnknown format type format.front() == '.'wb MB written in /__w/ml-builds/ml-builds/xgboost/src/data/../collective/allreduce.hCheck failed: validInput data contains `inf` or a value too large, while `missing` is not set to `inf`/__w/ml-builds/ml-builds/xgboost/src/data/../data/proxy_dmatrix.hUnknown type: Check failed: !at_end_n_prefetch_batches > 0total batches:Check failed: curr_exce_Waitn_prefetch_batches <= kPrefetchesfetch_it < cache_info_->offset.size()std::count_if(ring_->cbegin(), ring_->cend(), [](auto const& f) { return f.valid(); }) == n_prefetch_batchesSparse DMatrix assumes forward iteration.Check failed: !(*ring_)[count_].valid()cache_info_->offset.size() == n_batches_ + 1count_ == n_batches_Check failed: proxy_this->count_ >= 1source_->Iter() == this->count_Check failed: fmt->Read(page.get(), fi.get())St19__shared_ptr_accessIN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt19__shared_ptr_accessIN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt19__shared_ptr_accessIN7xgboost4data15ColumnarAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt12__shared_ptrIN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt12__shared_ptrIN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt12__shared_ptrIN7xgboost4data15ColumnarAdapterELN9__gnu_cxx12_Lock_policyE2EEN7xgboost10SparsePageEN7xgboost7DMatrixEN7xgboost4data11FileAdapterESt12bad_any_castSt10shared_ptrIN7xgboost4data15CSRArrayAdapterEESt10shared_ptrIN7xgboost4data12ArrayAdapterEESt10shared_ptrIN7xgboost4data15ColumnarAdapterEEN7xgboost17BatchIteratorImplINS_11EllpackPageEEEN7xgboost4data20SparsePageSourceImplINS_11EllpackPageEEEN7xgboost4data18PageSourceIncMixInINS_11EllpackPageEEEN7xgboost4data17EllpackPageSourceENSt13__future_base7_ResultISt10shared_ptrIN7xgboost10SparsePageEEEEZN7xgboost6common10ThreadPool6SubmitIZNS_4data20SparsePageSourceImplINS_10SparsePageEE9ReadCacheEvEUlvE_St10shared_ptrIS5_EEEDaOT_EUlvE_St15_Sp_counted_ptrIPN7xgboost6common12MmapResourceELN9__gnu_cxx12_Lock_policyE2EENSt13__future_base13_State_baseV27_SetterISt10shared_ptrIN7xgboost10SparsePageEEOS5_EESt23_Sp_counted_ptr_inplaceIN7xgboost10SparsePageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseISt10shared_ptrIN7xgboost10SparsePageEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EE OOOOAAGGGG/src/data/./sparse_page_source.hlabels_lower_boulabels_upper_bouP?/__w/ml-builds/ml-builds/xgboost/src/data/ellpack_page.ccInternal Error: XGBoost is not compiled with CUDA but EllpackPage is requiredCheck failed: parser_name_args_cache.size() <= 2name_args.size() == 2Invalid uri argument format for key in arg for value in arg /__w/ml-builds/ml-builds/xgboost/src/data/file_iterator.ccOnly one `#` is allowed in file path for cachefile specificationURI parameter `format` is required for loading text data: filename?format=csvCheck failed: std::getline(is, kv.first, '=')Check failed: std::getline(is, kv.second)/__w/ml-builds/ml-builds/xgboost/src/data/../common/hist_util.h/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index.ccCheck failed: this->data.empty()Check failed: resource->Type() == common::ResourceHandler::kMalloc/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index.hhit_count.size() == n_bins_totalCheck failed: p_fmat->SingleColBlock()(J(J LKXK,KKEJJJEGGIxIhIXIHIF(IH8IFFFHHHHhHPH8HHGGNN8PPOOhPPPxPOxOOQQRRRRxR`RHR(RRQCheck failed: columns_n_bytes >= this->data.size()Check failed: malloc_resourceCheck failed: !sorted_sketchrow_ptr.size() == 0/__w/ml-builds/ml-builds/xgboost/src/data/../common/io.h/__w/ml-builds/ml-builds/xgboost/src/data/../common/ref_resource_view.hVV ]\\\\x\X\8\\[xYxY[x[X[8[[ZZZZhZ W W(YYXXXXhXHX(XWH`H````x`8`(``__X`haha8ccbbbbbbhbHb8e8e(eeexeeheddcHehfhf(hhgggggxgXg8gPrPr rqqxr@rqqoprq8o8oonnxnhnoXn0lnommmmmmxmhmXm@m8lnpppppxphpPp8pp0op/__w/ml-builds/ml-builds/xgboost/src/data/../common/column_matrix.hCheck failed: storage.Resource()->Type() == ResourceHandler::kMalloc[Internal Error]: Cannot grow the vector when external memory is used.m_size >= storage.size()Check failed: resourcenum_nonzeros_.size() == n_features?/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index_format.ccCheck failed: binTypeSize == kUint8BinsTypeSize || binTypeSize == kUint16BinsTypeSize || binTypeSize == kUint32BinsTypeSizeCheck failed: fiRaw GHistIndex binary data format.N7xgboost4data16SparsePageFormatINS_16GHistIndexMatrixEEEN7xgboost4data19GHistIndexRawFormatE*N7xgboost4dataUlvE_Ecount_ == source_->Iter()cuts_.Values().size() != 0/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.h/__w/ml-builds/ml-builds/xgboost/src/data/proxy_dmatrix.h/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_writer.h/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index_page_source.ccN7xgboost17BatchIteratorImplINS_16GHistIndexMatrixEEEN7xgboost4data20SparsePageSourceImplINS_16GHistIndexMatrixEEEN7xgboost4data18PageSourceIncMixInINS_16GHistIndexMatrixEEEN7xgboost4data23GradientIndexPageSourceENSt13__future_base7_ResultISt10shared_ptrIN7xgboost16GHistIndexMatrixEEEEZN7xgboost6common10ThreadPool6SubmitIZNS_4data20SparsePageSourceImplINS_16GHistIndexMatrixEE9ReadCacheEvEUlvE_St10shared_ptrIS5_EEEDaOT_EUlvE_NSt13__future_base13_State_baseV27_SetterISt10shared_ptrIN7xgboost16GHistIndexMatrixEEOS5_EESt15_Sp_counted_ptrIPN7xgboost16GHistIndexMatrixELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost16GHistIndexMatrixESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseISt10shared_ptrIN7xgboost16GHistIndexMatrixEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EE/src/data/sparsePzPz|{{{{`{@{ {{zhP0 ؅I( 눶Јx[40ЋpPЎxX@ @@Бp`H(p@`蓶蓶ДpP8`ؓؓ0Е`@pP0ЛhHHX0ОpP(СpP0蠶 ਸ਼`ȥȥxh襶XXX@ শаpPhXحHHpH0讶ЮиpPhXص@@pH0趶жp¶p¶ĶöööööpöPö0ööttuuuu vv@vhu u@uvv@xxwwwwpwPw0ww@y@yT{,{ {zzzz\z8zy||~}}}@~(~`~}P}p}~~`8 h@Ȃ @x0P@hH Їp臷 X0 hH(XXЍ@ 88Ќ`@ Ћxx`8 hX0hИX0X@@P ЛX088(P؟РPȞhP8 h@(袷Ȣp@88(PاШPȦhP8 h@(誷Ȫp@88(PدаPȮhP8 h@(買Ȳp@/__w/ml-builds/ml-builds/xgboost/src/data/iterative_dmatrix.ccpage.row_ptr.size() == h_offset.size()/__w/ml-builds/ml-builds/xgboost/src/data/../common/../data/../common/hist_util.href->Info().num_col_ == n_featuresInvalid ref DMatrix, different number of features.param.max_bin == batch_.max_binInconsistent `max_bin`. `max_bin` should be the same across different QuantileDMatrix, and consistent with the Booster being trained.Check failed: !param.regen && param.hess.empty()Check failed: !detail::RegenGHist(param, batch_)`QuantileDMatrix` not initialized.`sparse_threshold` can not be changed when `QuantileDMatrix` is used instead of `DMatrix`.Inconsistent number of columns.Check failed: std::none_of(column_sizes.cbegin(), column_sizes.cend(), [&](auto f) { return f > accumulated_rows; })Something went wrong during iteration.Data must has at least 1 column.accumulated_rows == Info().num_row_this->ghist_->Features() == Info().num_col_proxy->Info().labels.Size() == 0Iterative DMatrix must have at least 1 batch.ȱȱ買Ȳ0h(@((hH(೷xxxX8ȷ෷ضصصX0ظpHX÷0÷÷÷····x·X·ϷϷPѷ(ѷѷззззhзHззѷѷBӷӷҷҷҷҷvҷUҷ2ҷҷڷڷ8ܷܷܷ۷۷۷۷h۷H۷(۷ܷܷH޷޷ݷݷݷݷxݷXݷ8ݷݷCheck failed: refCheck failed: p_cutsh_ft.size() == n_ftn_features == num_cols()n_features >= 1Check failed: p_sketchh_ft.size() == n_featuresrbegin == Info().num_row_/__w/ml-builds/ml-builds/xgboost/src/data/simple_batch_iterator.hCheck failed: page_ != nullptr/__w/ml-builds/ml-builds/xgboost/src/data/iterative_dmatrix.hSlicing DMatrix is not supported for Quantile DMatrix.Slicing DMatrix columns is not supported for Quantile DMatrix.Not implemented for `QuantileDMatrix`.Only `hist` and `gpu_hist` tree method can use `QuantileDMatrix`./__w/ml-builds/ml-builds/xgboost/src/data/../common/../data/../common/threading_utils.h/__w/ml-builds/ml-builds/xgboost/src/data/../common/../data/gradient_index.hCheck failed: proxy_handleInvalid proxy handle.Check failed: typedCheck failed: !std::isnan(sparse_thresh)VVVlV\VLV= 2Generating new Ellpack page.invalid input file formattmagic == kMagic/__w/ml-builds/ml-builds/xgboost/src/data/batch_utils.hBatch parameter is not initialized.batch_param_.max_bin == param.max_binCheck failed: !detail::RegenGHist(batch_param_, param)Inconsistent sparse threshold.Generating new Gradient Index.batch_param_.hess.data() == param.hess.data()/__w/ml-builds/ml-builds/xgboost/src/data/../common/error_msg.hSample size too large for the current updater. Maximum number of samples:. Consider using a different updater or tree_method.Check failed: in_stream->Read(&tmagic)invalid format, magic number mismatch/__w/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.h/__w/ml-builds/ml-builds/xgboost/src/data/../collective/allgather.h/__w/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.ccCheck failed: (std::is_same::value || std::is_same::value)Expecting CSCAdapterN7xgboost7CSCPageEN7xgboost13SortedCSCPageEN7xgboost4data13SimpleDMatrixEN7xgboost17BatchIteratorImplINS_10SparsePageEEEN7xgboost4data23SimpleBatchIteratorImplINS_10SparsePageEEEN7xgboost17BatchIteratorImplINS_7CSCPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_7CSCPageEEEN7xgboost17BatchIteratorImplINS_13SortedCSCPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_13SortedCSCPageEEESt15_Sp_counted_ptrIPN7xgboost7CSCPageELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost13SortedCSCPageELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost11EllpackPageELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_7CSCPageEEELN9__gnu_cxx12_Lock_policyE2EEThe total number of elements should be multiple of the number of/src/data/simple/__w/ml-builds/ml-builds/xgboost/src/data/./../common/common.h/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.ccCheck failed: sparse_page_source_Check failed: ghist_index_source_Couldn't remove external memory cache file ; you may want to remove it manuallyCheck failed: iter_.Next()Must have at least 1 batch.-rinfo_.num_col_ != 0.gradient_index.pagecuts.Values().size() != 0this->Info().num_col_ != 0/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_dmatrix.hSlicing DMatrix is not supported for external memory.Slicing DMatrix columns is not supported for external memory.Can not obtain a single CSR page for external memory DMatrix/__w/ml-builds/ml-builds/xgboost/src/data/./proxy_dmatrix.hCheck failed: kv.secondthis->page_->Size() == n_features_this->page_->data.Size() == csr->data.Size()Make cache:N7xgboost4data20SparsePageSourceImplINS_10SparsePageEEEN7xgboost4data16SparsePageSourceEN7xgboost4data20SparsePageSourceImplINS_7CSCPageEEEN7xgboost4data18PageSourceIncMixInINS_7CSCPageEEEN7xgboost4data13CSCPageSourceEN7xgboost4data20SparsePageSourceImplINS_13SortedCSCPageEEEN7xgboost4data18PageSourceIncMixInINS_13SortedCSCPageEEEN7xgboost4data19SortedCSCPageSourceEN7xgboost4data17SparsePageDMatrixENSt13__future_base7_ResultISt10shared_ptrIN7xgboost7CSCPageEEEENSt13__future_base7_ResultISt10shared_ptrIN7xgboost13SortedCSCPageEEEEN7xgboost16GHistIndexMatrixEZN7xgboost6common10ThreadPool6SubmitIZNS_4data20SparsePageSourceImplINS_7CSCPageEE9ReadCacheEvEUlvE_St10shared_ptrIS5_EEEDaOT_EUlvE_ZN7xgboost6common10ThreadPool6SubmitIZNS_4data20SparsePageSourceImplINS_13SortedCSCPageEE9ReadCacheEvEUlvE_St10shared_ptrIS5_EEEDaOT_EUlvE_NSt13__future_base13_State_baseV27_SetterISt10shared_ptrIN7xgboost7CSCPageEEOS5_EENSt13__future_base13_State_baseV27_SetterISt10shared_ptrIN7xgboost13SortedCSCPageEEOS5_EESt15_Sp_counted_ptrIPN7xgboost4data5CacheELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data23GradientIndexPageSourceELN9__gnu_cxx12_Lock_policyE2EENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7xgboost6common10ThreadPoolC4EiEUlvE_EEEEEESt23_Sp_counted_ptr_inplaceIN7xgboost4data16SparsePageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data13CSCPageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data19SortedCSCPageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost7CSCPageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseISt10shared_ptrIN7xgboost7CSCPageEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost13SortedCSCPageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseISt10shared_ptrIN7xgboost13SortedCSCPageEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EE.sorted.col.page/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_raw_format.ccCheck failed: page.offset.Size() != 0 && offset_vec[0] == 0offset_vec.back() == page.data.Size()Raw binary data format.page->offset.Size() != 0UInvalid SparsePage fileN7xgboost4data16SparsePageFormatINS_10SparsePageEEEN7xgboost4data19SparsePageRawFormatINS_10SparsePageEEEN7xgboost4data16SparsePageFormatINS_7CSCPageEEEN7xgboost4data19SparsePageRawFormatINS_7CSCPageEEEN7xgboost4data16SparsePageFormatINS_13SortedCSCPageEEEN7xgboost4data19SparsePageRawFormatINS_13SortedCSCPageEEE*N7xgboost4dataUlvE_E*N7xgboost4dataUlvE0_E*N7xgboost4dataUlvE1_Egpu_coord_descentLinear booster does not support prediction range.Linear booster, implement generalized linear model.layer_begin == 0GBLinearTrainParam/__w/ml-builds/ml-builds/xgboost/include/xgboost/gbm.hSlice is not supported by the current booster.Inplace predict is not supported by the current booster./__w/ml-builds/ml-builds/xgboost/src/gbm/gblinear.ccgblinear does not support prediction of leaf indexmodel/__w/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.hfi->Read(¶m_, sizeof(param_)) == sizeof(param_)DoBoost`gblinear`Check failed: !p_fmat->Info().HasCategorical() doesn't support categorical features.get(in["name"]) == "gblinear"/__w/ml-builds/ml-builds/xgboost/src/gbm/../common/threading_utils.hCheck failed: !model_.weight.empty()gblinear doesn't support number of trees for feature importance.gblinear only has `weight` defined for feature importance.Model is not initializedCheck failed: trees.empty()importance_type == "weight"PredictBatchInternalbase_margin.Size() == nsize * ngroup { "bias": [ ], "weight": [ ] }bias: weight: shotguntolerancemax_row_perbatchMaximum rows per batch.Update algorithm for linear model. One of shotgun/coord_descentStop if largest weight update is smaller than this number.gblinear_train_paramCheck failed: this->updater_/__w/ml-builds/ml-builds/xgboost/src/gbm/../common/common.hdevice="cuda", updater="coord_descent"GBLinearN7xgboost5ModelEN7xgboost12ConfigurableEN7xgboost15GradientBoosterEN7xgboost3gbm8GBLinearE*N7xgboost3gbmUlPKNS_17LearnerModelParamEPKNS_7ContextEE_Eboosted_roundsN7xgboost3gbm13GBLinearModelEDeprecatedGBLinedeprecated_num_fint (non-negativdeprecated_num_oUnknown gbm type /__w/ml-builds/ml-builds/xgboost/src/gbm/gbm.cc/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree.cc/__w/ml-builds/ml-builds/xgboost/src/gbm/../tree/../common/threading_utils.h/__w/ml-builds/ml-builds/xgboost/src/gbm/../data/proxy_dmatrix.hCheck failed: !updaters_.empty()model_.param.num_parallel_tree == trees.size()model_.param.num_parallel_tree == 1Boosting random forest is not supported for current objective.Check failed: !trees.front()->IsMultiTarget() support for multi-target tree is not yet implemented.trees.size() == model_.param.num_parallel_treetree_end <= model_.trees.size()The requested feature doesn't have SYCL specific implementation yet. Inplace predict accepts only DMatrixProxy as input.Unknown data type for inplace prediction:get(in["name"]) == "gbtree"Check failed: this->model_.learner_model_param->Initialized()this->model_.trees_to_update.size() == this->model_.trees.size() trees remain. Slice the model before making update if you only want to update a portion of trees.out_model.iteration_indptr.front() == 0Number of features used for training and prediction.Number of parallel trees constructed during each iteration. This option is used to support boosted random forest.Check failed: !updaters_.front()->CanModifyTree()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 roundsMismatching size between number of rows from input data and size of gradient vector.Check failed: tparam_.tree_method == TreeMethod::kHist || tparam_.tree_method == TreeMethod::kAutoOnly the hist tree method is supported for building multi-target trees with vector leaf.GPU is not yet supported for vector leaf.Current objective doesn't support external memory.in_gpair->Size() % n_groups == 0Umust have exactly ngroup * nrow gpairs Loading from a raw memory buffer (like pickle in Python, RDS in R) on a CPU-only machine. Consider using `save_model/load_model` instead. See: https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html for more details about differences between saving model and serializing. Changing `tree_method` to `hist`./__w/ml-builds/ml-builds/xgboost/src/gbm/../common/error_msg.hIf you are loading a serialized model (like pickle in Python, RDS in R) or configuration generated by an older version of XGBoost, please export the model by calling `Booster.save_model` from that version first, then load it back in current version. See: https://xgboost.readthedocs.io/en/stable/tutorials/saving_model.html for more details about differences between saving model and serializing. Changing updater from `grow_gpu_hist` to `grow_quantile_histmaker`.The `exact` tree method is not supported on GPU.Tree booster, gradient boosted trees.h_tmp.Size() == h_in.Size()Check failed: cpu_predictor_Update tree leafout_preds->version == 0Invalid number of trees.CPU implementation is usedUnknown device type:Check failed: p_gbtreeend != beginEmpty slice is not allowed.Not all trees are updated, GBTreeModelParamnum_treesGBTreeTrainParamDartTrainParamgbtree_train_paramspecified_updaterUpdater: `` n_out % gpair->Size() == 0gpair->Size() == n_outCheck failed: ctx_->IsCPU()BoostNewTreesn_groups != 0grow_gpu_histgrow_quantile_histmakercpu_predictorUsing tree method: grow_histmakergrow_colmaker,pruneUnknown tree_method: `Tree booster, dart./__w/ml-builds/ml-builds/xgboost/src/gbm/../tree/../common/common.hweight_drop/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.hiteration_indptr.size() == 1/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree.hCheck failed: !model.iteration_indptr.empty()end <= model.BoostedRounds()Out of range for tree layers.tree_begin <= tree_endtree_begin == 0Predict interaction contribution supports only iteration end: (0, n_iteration), using model slicing instead.Predict contribution supports only iteration end: (0, n_iteration), using model slicing instead.Predict leaf supports only iteration end: (0, n_iteration), use model slicing instead.step >= 1out_l == n_layersget(in["name"]) == "dart"Check failed: !this->model_.learner_model_param->IsVectorLeaf()p_out_preds->predictions.Size() == predts.predictions.Size()Check failed: predictori >= p_out_preds->versionCheck failed: successUnsupported data type for inplace predict.predts.predictions.Size() == p_out_preds->predictions.Size()Check failed: tree_param_.GetInitialised()drop trees, weight = Check failed: p_dartCheck failed: p_dart->weight_drop_.empty()updater_seqTree updater sequence.process_typedefaultupdatetree_methodapproxexactWhether to run the normal boosting process that creates new trees, or to update the trees in an existing model.Choice of tree construction method.sample_typeuniformweightednormalize_typeforestrate_dropone_dropskip_dropDifferent types of sampling algorithm.Different types of normalization algorithm.Fraction of trees to drop during the dropout.Whether at least one tree should always be dropped during the dropout.Probability of skipping the dropout during a boosting iteration.dart_train_paramXPZYX[Y*N7xgboost3gbmUlPKNS_17LearnerModelParamEPKNS_7ContextEE_E*N7xgboost3gbmUlPKNS_17LearnerModelParamEPKNS_7ContextEE0_Eidx <= total_n_treesInvalid tree index.total_gaintotal_coverUnknown feature importance type, expected one of: {"weight", "total_gain", "total_cover", "gain", "cover"}, got: N4dmlc9parameter10FieldEntryIN7xgboost10TreeMethodEEEN4dmlc9parameter10FieldEntryIN7xgboost15TreeProcessTypeEEEN7xgboost3gbm6GBTreeEN7xgboost3gbm4DartE?A;layer_trees != 0GBTree: invalid model fileiteration_indptr/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.ccparam.num_trees == static_cast(trees.size())model.trees.size() == model.param.num_treesmodel.tree_info.size() == model.param.num_treesmodel.iteration_indptr.back() == model.param.num_treesCheck failed: !iteration_indptr.empty()iteration_indptr.back() == param.num_treesparam.num_trees == static_cast(trees.size())fi->Read(¶m, sizeof(param)) == sizeof(param)fi->Read(dmlc::BeginPtr(tree_info), sizeof(int32_t) * param.num_trees) == sizeof(int32_t) * param.num_treestrees_json.size() == param.num_treestree_info_json.size() == param.num_treesN7xgboost3gbm11GBTreeModelEgbtree_model_pariteration_indptrFlag to print out detailed breakdown of runtime.Whether to use RAPIDS Memory Manager to allocate GPU memory in XGlobalConfigurat/__w/ml-builds/ml-builds/xgboost/src/learner.ccmulti-target-multi-class is not yet supported. Output classes:Check failed: std::as_const(base_score_).Data()->HostCanRead()Model is not yet initialized (not fitted).Check failed: base_score_.Data()->HostCanRead()Check failed: base_score_.Data()->DeviceCanRead()base_score_.Data()->DeviceCanRead() == that.base_score_.Data()->DeviceCanRead(), output targets:base_score_.Size() == 1LearnerModelParamLegacyLearnerTrainParamCheck failed: learner_model_param_.Initialized()learner_model_param_.BaseScore(this->Ctx()).Size() != 0Check failed: !this->need_configuration_/__w/ml-builds/ml-builds/xgboost/include/xgboost/objective.hmultioutput is not supported by the current objective function/__w/ml-builds/ml-builds/xgboost/include/xgboost/cache.hqueue_.size() == container_.size()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_Check failed: ret.ec == std::errc{}num_featurenum_classnum_targetboost_from_averageCall Configure before saving model.learner_model_paramobjectiveattributesfeature_typesModelConfig/__w/ml-builds/ml-builds/xgboost/src/collective/../data/../common/error_msg.hGlobal bias of the model.int (non-negative)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.Number of output targets. Can be set automatically if not specified.Whether we should calculate the base score from training data.disable_default_eval_metricreg:squarederrormulti_strategyone_output_per_treemulti_output_treeFlag to disable default metric. Set to >0 to disableGradient booster used for training.Objective function used for obtaining gradient.Strategy used for training multi-target models. `multi_output_tree` means building one single tree for all targets.multi:softprobnum_output_groupmulti:softmaxcount:poisson0.7learner_train_parammetricsgeneric_paramCheck failed: !this->learner_model_param_.IsVectorLeaf()Please use JSON/UBJ format for model serialization with multi-output models.feature names and feature types are being disregarded, use JSON/UBJSON format instead.;binfUnsupported prediction type:Check failed: it != container_.cend()remained.size() + expired.size() == container_.size()Check failed: this->obj_Inconsistent labels.Check failed: ptrCheck failed: n_targets == t || 1 == tCheck failed: n_targets == 1 || n_targets == mparam_.num_targetInconsistent configuration of num_target. Configuration result from input data:, configuration from parameter:Check failed: tparam_.GetInitialised()learner_model_param_.BaseScore(Ctx()).Size() != 0Check failed: IsA(in)Invalid version string in configget(objective_fn["name"]) == tparam_.objectiveFound JSON model saved before XGBoost 1.6, please save the model using current version again. The support for old JSON model will be discontinued in XGBoost 2.3.Check failed: that.lock_.try_lock()/__w/ml-builds/ml-builds/xgboost/src/collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/collective/allreduce.hCheck failed: matrix.first.ptrCheck failed: !matrix.second.ref.expired()Unfortunately, XGBoost does not support data matrices with 0 feature is supplied. Are you using raw Booster interface?n_features <= max_n_features features or greatermparam_.num_feature != 0/__w/ml-builds/ml-builds/xgboost/src/collective/aggregator.hbase_score.Size() == 1Check failed: !std::isnan(mparam_.base_score)Check failed: std::equal(data.cbegin(), data.cend(), sync.cbegin())Different model parameter across workers.Check failed: !std::isinf(mparam_.base_score)container_.size() < max_size__Map_base::atmultiple_predictions <= 1Check failed: gbm_ != nullptrPerform one kind of prediction at a time.Predict must happen after Load or configurationthis->learner_model_param_.OutputLength() == in_gpair->Shape(1)The number of columns in gradient should be equal to the number of targets/classes in the model.UpdateOneIterPredictRawPredictionsGetGradientGradientsLearnerCONFIG-offset:this->learner_model_param_.num_feature != 0out_impl->learner_model_param_.num_feature == this->learner_model_param_.num_featureout_impl->learner_model_param_.num_feature != 0begin >= 0best_iterationbest_scoreEvalOneIterInvalid parameter "" contains whitespace. Parameters: { ", } are not used. Configurefixed_size->Read(&buffer[0], size) == sizebs64header != "bs64"fp.Read(&header[0], 4) == 4UInvalid model formatcount_poisson_max_delta_stepmulti:%uBase64 format is no longer supported in brick.fi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_)BoostLearner: wrong model formatCheck failed: fi->Read(&tparam_.objective)Check failed: fi->Read(&tparam_.booster)data_.Size() == detail::CalcSize(shape_)Loading model from XGBoost < 1.0.0, consider saving it again for improved compatibilityInvalid serialization file.sz > 0fp.Read(&header[0], header.size()) == serialisation_header_.size()Check failed: header == serialisation_header_fp.Read(&sz, sizeof(sz)) == sizeof(sz)N4dmlc12SerializableEN7xgboost7LearnerEN4dmlc9parameter10FieldEntryIN7xgboost13MultiStrategyEEEN7xgboost20LearnerConfigurationEN7xgboost9LearnerIOEN7xgboost11LearnerImplESt23_Sp_counted_ptr_inplaceIN7xgboost20PredictionCacheEntryESaIS1_ELN9__gnu_cxx12_Lock_policyE2EEUnknown linear updater /__w/ml-builds/ml-builds/xgboost/src/linear/linear_updater.ccLearning rate ofL2 regularizatioL1 regularizatiofeature_selectorFeature selection or ordering meLinearTrainParamUpdate linear model according to coordinate descent algorithm./__w/ml-builds/ml-builds/xgboost/src/linear/../common/threading_utils.hUpdateFeatureCoordinateParam/__w/ml-builds/ml-builds/xgboost/src/linear/updater_coordinate.ccSave config for CPU updater.coordinate_param/__w/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.hunknown coordinate selector: .--8,0.N7xgboost13LinearUpdaterEN7xgboost6linear15FeatureSelectorEN7xgboost6linear21CyclicFeatureSelectorEN7xgboost6linear22ShuffleFeatureSelectorEN7xgboost6linear21RandomFeatureSelectorEN7xgboost6linear21GreedyFeatureSelectorEN7xgboost6linear22ThriftyFeatureSelectorEN7xgboost6linear17CoordinateUpdaterE*N7xgboost6linearUlvE_EThe number of top features to select in 'thrifty' feature_selector. The value of zero means using all the featurlinear_train_parCoordinateUpdateUpdate linear model according to shotgun coordinate descent algorithm./__w/ml-builds/ml-builds/xgboost/src/linear/updater_shotgun.ccUnsupported feature selector for shotgun updater. Supported options are: {cyclic, shuffle}$D|N7xgboost6linear14ShotgunUpdaterE*N7xgboost6linearUlvE_EWARNING: DEBUG: INFO: aucaucpr/__w/ml-builds/ml-builds/xgboost/src/metric/../common/common.hlabels.Size() == predts.size()Receiver Operating Characteristic Area Under the Curve.Area under PR curve for both classification and rank.Invalid group with less than 3 samples is found on worker . Calculating AUC value requires at least 2 pairs of samples.labels.Size() != 0auc <= 1.0 + kRtEps/__w/ml-builds/ml-builds/xgboost/src/metric/../common/threading_utils.h/__w/ml-builds/ml-builds/xgboost/src/metric/auc.ccinfo.group_ptr_.size() >= 2/__w/ml-builds/ml-builds/xgboost/src/metric/../collective/allreduce.hn_classes != 0AUC doesn't support multi-target model./__w/ml-builds/ml-builds/xgboost/src/metric/../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/metric/../collective/aggregator.h/__w/ml-builds/ml-builds/xgboost/src/metric/../common/algorithm.hinfo.weights_.Size() == info.group_ptr_.size() - 1info.group_ptr_.back() == info.labels.Size()Dataset is empty, or contains only positive or negative samples.Total AUC across groups: , valid groups: /__w/ml-builds/ml-builds/xgboost/src/metric/auc.hPR-AUC supports only binary relevance for learning to rank.N7xgboost6MetricEN7xgboost13MetricNoCacheEN7xgboost6metric7EvalAUCINS0_10EvalROCAUCEEEN7xgboost6metric10EvalROCAUCEN7xgboost6metric7EvalAUCINS0_9EvalPRAUCEEEN7xgboost6metric9EvalPRAUCE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E/src/metric/auc.??????zo ?mphequantilegamma-nloglikgamma-deviancepoisson-nloglikmapemaermslermse/__w/ml-builds/ml-builds/xgboost/src/metric/elementwise_metric.cuCheck failed: param != nullptrtweedie-nloglik must be in format tweedie-nloglik@rhoCheck failed: rho_ < 2 && rho_ >= 1tweedie variance power must be in interval [1, 2)sscanf(param, "%f", &threshold_) == 1unable to parse the threshold value for the error metricMean absolute percentage error.Negative loglikelihood for logistic regression.Negative loglikelihood for poisson regression.Residual deviance for gamma regression.Negative log-likelihood for gamma regression.tweedie-nloglik@rho for tweedie regression.tweedie-nloglik@%fRooted mean square error.Rooted mean square log error.Mean absolute error.Mean Pseudo-huber error.Binary classification error.tweedie-nloglikQuantile regression error.quantile_loss_parampseudo_huber_paramname == "quantile"/__w/ml-builds/ml-builds/xgboost/src/metric/../common/quantile_loss_utils.hCheck failed: GetInitialised()Check failed: !quantile_alpha.Get().empty()quantile alpha must be in the range [0.0, 1.0].Check failed: !alpha_.Empty()dat[1] > 0n_targets != 0info.labels.Shape(0) == info.num_row_slope for pseudo huber cannot be 0.slope != 0.0preds.Size() == info.labels.Size()label and prediction size not match, hint: use merror or mlogloss for multi-class classificationinfo.labels.Shape(1) != 0N7xgboost6metric15PseudoErrorLossEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowRMSEEEEN7xgboost6metric13EvalEWiseBaseINS0_12EvalRowRMSLEEEEN7xgboost6metric13EvalEWiseBaseINS0_10EvalRowMAEEEEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowMAPEEEEN7xgboost6metric13EvalEWiseBaseINS0_14EvalRowLogLossEEEN7xgboost6metric13EvalEWiseBaseINS0_20EvalPoissonNegLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_17EvalGammaDevianceEEEN7xgboost6metric13EvalEWiseBaseINS0_16EvalGammaNLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_9EvalErrorEEEN7xgboost6metric13EvalEWiseBaseINS0_18EvalTweedieNLogLikEEEN7xgboost6metric13QuantileErrorE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E*N7xgboost6metricUlPKcE1_E*N7xgboost6metricUlPKcE2_E*N7xgboost6metricUlPKcE3_E*N7xgboost6metricUlPKcE4_E*N7xgboost6metricUlPKcE5_E*N7xgboost6metricUlPKcE6_E*N7xgboost6metricUlPKcE7_E*N7xgboost6metricUlPKcE8_E*N7xgboost6metricUlPKcE9_E*N7xgboost6metricUlPKcE10_E@$tI$tɕ$pseudo_huber_parư>/__w/ml-builds/ml-builds/xgboost/src/metric/metric.ccUnknown metric function merrormloglossMulticlass classification error.Multiclass negative loglikelihood./__w/ml-builds/ml-builds/xgboost/src/metric/multiclass_metric.cuCheck failed: preds.Size() % info.labels.Size() == 0label and prediction size not matchmlogloss and merror are only used for multi-class classification, use logloss for binary classificationCheck failed: label_error >= 0 && label_error < static_cast(n_class)MultiClassEvaluation: label must be in [0, num_class),preds.Size() == 0nclass >= 1U num_class= but found in labelN7xgboost6metric14EvalMClassBaseINS0_14EvalMatchErrorEEEN7xgboost6metric14EvalMatchErrorEN7xgboost6metric14EvalMClassBaseINS0_16EvalMultiLogLossEEEN7xgboost6metric16EvalMultiLogLossE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E]Bcox-nloglikNegative log partial likelihood of Cox proportional hazards model.Invalid output score, might be caused by invalid query group weight.AMS metric for higgs.preprecision@k for rank.map@k for ranking.ndcg@k for ranking.score <= 1.0 + kRtEps/__w/ml-builds/ml-builds/xgboost/src/metric/rank_metric.ccCheck failed: !collective::IsDistributed()Cox metric does not support distributed evaluationAMS must be in format ams@kams@/__w/ml-builds/ml-builds/xgboost/src/metric/../common/ranking_utils.hCheck failed: param_.GetInitialised()Groups() == info.weights_.Size()the size of label.weight.weights.size() == p_cache->Groups()metric AMS do not support distributed evaluationbest-ams-ratio=||~|lambdarank_paramCheck failed: p_cache->Param() == param_St23_Sp_counted_ptr_inplaceIN7xgboost3ltr8MAPCacheESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost3ltr9NDCGCacheESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost3ltr8PreCacheESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEN7xgboost6metric7EvalAMSEN7xgboost6metric7EvalCoxEN7xgboost6metric17EvalRankWithCacheINS_3ltr8PreCacheEEEN7xgboost6metric13EvalPrecisionEN7xgboost6metric17EvalRankWithCacheINS_3ltr9NDCGCacheEEEN7xgboost6metric8EvalNDCGEN7xgboost6metric17EvalRankWithCacheINS_3ltr8MAPCacheEEEN7xgboost6metric12EvalMAPScoreE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E*N7xgboost6metricUlPKcE1_E*N7xgboost6metricUlPKcE2_E*N7xgboost6metricUlPKcE3_Elambdarank_paramA@@aft-nloglikinterval-regression-accuracyNegative log likelihood of Accelerated Failure Time model./__w/ml-builds/ml-builds/xgboost/src/metric/survival_metric.cuCheck failed: metric_AFT metric must be configured first, with distribution type and scaleUnknown probability distributionpreds.Size() == info.labels_lower_bound_.Size()preds.Size() == info.labels_upper_bound_.Size()ndata == labels_upper_bound.Size()N7xgboost6metric20AFTNLogLikDispatcherEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common18NormalDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common20LogisticDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common19ExtremeDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_30EvalIntervalRegressionAccuracyEEE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E-q=' @;f?k + 1 < h_node_ptr.size()y_idx <= info.labels.Shape(1)nptr.size() > 0n_unique == n_leaf/__w/ml-builds/ml-builds/xgboost/src/objective/../common/threading_utils.h/__w/ml-builds/ml-builds/xgboost/src/objective/../collective/../data/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/objective/adaptive.cc/__w/ml-builds/ml-builds/xgboost/src/objective/../common/stats.hCheck failed: h_row_set.empty()begin_pos <= sorted_pos.size()Check failed: !position.empty()h_node_ptr.back() <= info.num_row_/__w/ml-builds/ml-builds/xgboost/src/objective/../collective/aggregator.h/__w/ml-builds/ml-builds/xgboost/src/objective/../collective/allreduce.h/__w/ml-builds/ml-builds/xgboost/src/objective/../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/objective/adaptive.hCheck failed: quantiles.empty() || quantiles.size() == n_leafCheck failed: tree[nidx].IsLeaf()/__w/ml-builds/ml-builds/xgboost/src/objective/../common/algorithm.h H" 4(uhuu8vPu/__w/ml-builds/ml-builds/xgboost/src/objective/../common/transform.hNot part of device code. WITH_CUDA: /__w/ml-builds/ml-builds/xgboost/src/objective/aft_obj.cuinfo.labels_lower_bound_.Size() == ndatainfo.labels_upper_bound_.Size() == ndataNumber of weights should be equal to number of data points.info.weights_.Size() == ndataUnrecognized distributionsurvival:aftAFT loss functionN7xgboost3obj6AFTObjE*N7xgboost3objUlvE_E..@ؗҜ<@@pApHinge loss. Expects labels to be in [0,1f]/__w/ml-builds/ml-builds/xgboost/src/objective/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/objective/init_estimation.hinfo.weights_.Size() == info.num_row_/__w/ml-builds/ml-builds/xgboost/src/objective/hinge.cuinfo.labels.Size() == preds.Size()Invalid shape of labels.binary:hingeN7xgboost3obj8HingeObjE*N7xgboost3objUlvE_EN7xgboost3obj12FitInterceptE/__w/ml-builds/ml-builds/xgboost/src/objective/lambdarank_obj.cch_n_rel.size() == label.Size()LambdaRank with NDCG loss as objectiveLambdaRank with RankNet loss as objectiveLambdaRank with MAP loss as objective.h_n_rel.size() == gptr.back()rank:ndcgrank:pairwiserank:map/__w/ml-builds/ml-builds/xgboost/src/objective/../common/ranking_utils.hUnreachable.info.labels.Shape(1) <= 1multi-output for LTR is not yet supported.info.labels.Shape(1) == 1multi-target for learning to rank is not yet supported./__w/ml-builds/ml-builds/xgboost/src/objective/lambdarank_obj.hg_rank.size() == g_label.Size()؂Hxx ԸDtt@pp$<%l%l&%Z8[h[h\[Đ4dd 0``,\\info.labels.Size() == predt.Size()The size of label doesn't match the size of prediction.iter == 0ti+tj-St23_Sp_counted_ptr_inplaceIN7xgboost3ltr12RankingCacheESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEN7xgboost3obj13LambdaRankObjINS0_14LambdaRankNDCGENS_3ltr9NDCGCacheEEEN7xgboost3obj14LambdaRankNDCGEN7xgboost3obj13LambdaRankObjINS0_13LambdaRankMAPENS_3ltr8MAPCacheEEEN7xgboost3obj13LambdaRankMAPEN7xgboost3obj13LambdaRankObjINS0_18LambdaRankPairwiseENS_3ltr12RankingCacheEEEN7xgboost3obj18LambdaRankPairwiseE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_E*N7xgboost3objUlvE1_E{Gz?^7ffBff•f%Softmax for multi-class classification, output class index.Softmax for multi-class classification, output probability distribution./__w/ml-builds/ml-builds/xgboost/src/objective/multiclass_obj.cuCheck failed: preds.Size() == (static_cast(param_.num_class) * info.labels.Size())SoftmaxMultiClassObj: label size and pred size does not match. SoftmaxMultiClassObj: label must be in [0, num_class).label.Size() * num_class: preds.Size(): N7xgboost3obj20SoftmaxMultiClassObjE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_ENumber of output class in the multi-class classiSoftmaxMultiClassoftmax_multiclaҜ= n_alphasget(in["name"]) == Name()/__w/ml-builds/ml-builds/xgboost/src/objective/../common/quantile_loss_utils.hh_weights.size() == h_labels.Size()wtwwlx\w xhN7xgboost3obj18QuantileRegressionE*N7xgboost3objUlvE_E/__w/ml-builds/ml-builds/xgboost/src/objective/regression_obj.cureg:linear is now deprecated in favor of reg:squarederror.Scale the weight of positive examples by this factorMaximum delta step we allow each weight estimation to be. This parameter is required for possion regression.Tweedie variance power. Must be between in range [1, 2).Regression with squared error.Regression with root mean squared logarithmic error.Logistic regression for probability regression task.Logistic regression for binary classification task.Logistic regression for classification, output score before logistic transformation.Gamma regression using the gamma deviance loss with log link.Regression Pseudo Huber error.Poisson regression for count data.Cox regression for censored survival data (negative labels are considered censored).Tweedie regression for insurance data.RegLossParamscale_pos_weightPoissonRegressionParamTweedieRegressionParamtweedie_variance_powerreg:squaredlogerrorreg:logisticbinary:logisticbinary:logitrawreg:gammareg:linearMean absoluate error./__w/ml-builds/ml-builds/xgboost/src/objective/./regression_loss.hCheck failed: base_score > 0.0f && base_score < 1.0fbase_score must be in (0,1) for logistic loss, got: reg:absoluteerrorStringView{get(in["name"])} == StringView{"reg:absoluteerror"}info.labels.Size() != 0Ulabel set cannot be emptylabels are not correctly providedCheck failed: last_abs_y <= abs_yCoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed!survival:coxreg:tweedietweedie_regression_paramreg:pseudohubererrorpoisson_regression_paramPoissonRegression: label must be nonnegativeTweedieRegression: label must be nonnegativebase_margin->Size() == 1Sum of weights is close to 0.0, skipping base score estimation.reg_loss_paramlabel must be positive for gamma regression.label must be in [0,1] for logistic regressionlabel must be greater than -1 for rmsle so that log(label + 1) can be valid.N7xgboost3obj10RegLossObjINS0_16LinearSquareLossEEEN7xgboost3obj10RegLossObjINS0_15SquaredLogErrorEEEN7xgboost3obj10RegLossObjINS0_18LogisticRegressionEEEN7xgboost3obj10RegLossObjINS0_22LogisticClassificationEEEN7xgboost3obj10RegLossObjINS0_11LogisticRawEEEN7xgboost3obj10RegLossObjINS0_13GammaDevianceEEEN7xgboost3obj21PseudoHuberRegressionEN7xgboost3obj17PoissonRegressionEN7xgboost3obj13CoxRegressionEN7xgboost3obj17TweedieRegressionEN7xgboost3obj17MeanAbsoluteErrorE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_E*N7xgboost3objUlvE1_E*N7xgboost3objUlvE2_E*N7xgboost3objUlvE3_E*N7xgboost3objUlvE4_E*N7xgboost3objUlvE5_E*N7xgboost3objUlvE6_E*N7xgboost3objUlvE7_E*N7xgboost3objUlvE8_E*N7xgboost3objUlvE9_E*N7xgboost3objUlvE10_Epoisson_regressitweedie_regressiư>H9X989(94:D:99:gghhxiii^8jhjj^__a`aPaaa_` aa_ZZ```p`P`0``_a_ddPdddeexchedxexcxcxcfXf8ffeeeedhd8l8lppp`pHp0ppooohqhqrrrr`r@r rrqqCheck failed: IsMultiTarget()Check failed: IsLeaf(nidx)Make predictions using CPU./__w/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.ccbase_margin.Shape(1) == ngroup/__w/ml-builds/ml-builds/xgboost/src/predictor/../collective/allreduce.hCheck failed: !model.learner_model_param->IsVectorLeaf()Predict interaction contributionCheck failed: !p_fmat->Info().IsColumnSplit()Predict interaction contribution support for column-wise data split is not yet implemented./__w/ml-builds/ml-builds/xgboost/src/predictor/../common/threading_utils.h/__w/ml-builds/ml-builds/xgboost/src/predictor/../data/proxy_dmatrix.h/__w/ml-builds/ml-builds/xgboost/include/xgboost/tree_model.h/__w/ml-builds/ml-builds/xgboost/include/xgboost/multi_target_tree_model.hLGLG\L,LLKKKtKLK$KJCheck failed: xgboost::collective::IsDistributed()column-split prediction is only supported for distributed trainingout_preds->size() == p_fmat->Info().num_row_ * model_.learner_model_param->num_output_groupout_preds->size() == p_fmat->Info().num_row_ * (tree_end_ - tree_begin_)Predict contributionngroup != 0ncolumns != 0Predict contribution support for column-wise data split is not yet implemented.predict instancePredict instance with column splitPredict leaf with column splitm->NumColumns() == model.learner_model_param->num_featureNumber of columns in data must equal to trained model.Check failed: !p_m->Info().IsColumnSplit()Inplace predict support for column-wise data split is not yet implemented.Predict DMatrix with column splitout_preds->size() == n_samples * n_groupsSt19__shared_ptr_accessIN7xgboost4data10CSRAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt19__shared_ptr_accessIN7xgboost4data12DenseAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt12__shared_ptrIN7xgboost4data12DenseAdapterELN9__gnu_cxx12_Lock_policyE2EESt12__shared_ptrIN7xgboost4data10CSRAdapterELN9__gnu_cxx12_Lock_policyE2EEN7xgboost9predictor12CPUPredictorESt10shared_ptrIN7xgboost4data12DenseAdapterEESt10shared_ptrIN7xgboost4data10CSRAdapterEE*N7xgboost9predictorUlPKNS_7ContextEE_E?/__w/ml-builds/ml-builds/xgboost/src/predictor/cpu_treeshap.ccunique_path[i].pweight == 0Unique path must have zero weightUnknown predictor type /__w/ml-builds/ml-builds/xgboost/src/predictor/predictor.ccmodel.learner_model_param->num_output_group != 0margin.Shape(0) == n_samplesmargin.Shape(1) == n_groupsInvalid shape of base_margin. Expected: (N7xgboost9PredictorE/__w/ml-builds/ml-builds/xgboost/src/tree/constraints.ccFailed to parse feature interaction constraint: newsize != 0With error: _/__w/ml-builds/ml-builds/xgboost/src/tree/../collective/allreduce.h/__w/ml-builds/ml-builds/xgboost/src/tree/fit_stump.cc/__w/ml-builds/ml-builds/xgboost/src/tree/../common/threading_utils.hCheck failed: h_sum.CContiguous()/__w/ml-builds/ml-builds/xgboost/src/tree/../common/common.hn_targets == gpair.Shape(1)ư>ư>/__w/ml-builds/ml-builds/xgboost/src/tree/hist/histogram.ccnodes_to_build.size() == valid_candidates.size()/__w/ml-builds/ml-builds/xgboost/src/tree/hist/../../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/tree/hist/param.ccCheck failed: *local_tree == ref_treedebug_synchronizCheck if all distributed tree are identical after tree constructmax_cached_hist_long (non-negatiMaximum number of nodes in CPU histogram cache. Only for internaHistMakerTrainPa/__w/ml-builds/ml-builds/xgboost/src/tree/multi_target_tree_model.ccCheck failed: this->IsLeaf(nidx)Collapsing a split node to leaf weight.Size() == this->NumTarget()weights_.size() >= next_nidx * weight.Size()parent_.size() == left_.size()split_idx < this->param_->num_featureparent_[nidx] != InvalidNodeId()p_weight.Size() == base_weight.Size()l_weight.Size() == left_weight.Size()r_weight.Size() == right_weight.Size()in_weight.Size() == weight_out.size()param_->size_leaf_vector > 1parent_.size() >= 1left_.size() == right_.size()nidx < left_.size()nidx < right_.size()nidx < parent_.size()nidx < split_index_.size()loss_changessum_hessianbase_weightssplit_indicessplit_conditionsdefault_leftparentsleft_childrenright_childrenN7xgboost15MultiTargetTreeE/__w/ml-builds/ml-builds/xgboost/src/tree/param.ccFound floating point number in interaction constraintsUnknown value type for interaction constraint:std::floor(d) == d/__w/ml-builds/ml-builds/xgboost/src/tree/tree_model.ccparam_.num_nodes == static_cast(nodes_.size())param_.num_nodes == static_cast(stats_.size())param_.deprecated_num_roots == 1Check failed: !IsMultiTarget()Please use JSON/UBJSON for saving models with multi-target trees.Check failed: !HasCategoricalSplit()Please use JSON/UBJSON for saving models with categorical splits.fmap.Size() <= std::numeric_limits::max()split_index < this->param_.num_featureCheck failed: this->p_mt_tree_fi->Read(¶m_, sizeof(TreeParam)) == sizeof(TreeParam)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(deleted_nodes_.size()) == param_.num_deletedthis->split_types_.size() == this->Size()this->GetSplitCategoriesPtr().size() == this->Size()get(out["tree_param"]["num_nodes"]) == std::to_string(param_.num_nodes)this->split_types_.size() == param_.num_nodesstatic_cast(deleted_nodes_.size()) == param_.num_deletedthis->split_categories_segments_.size() == param_.num_nodesDump text representation of treeDump json representation of treeDump graphviz representation of tree{param_.num_nodes != 0mean_values->size() > 0UCheck failed: node.IsLeaf()param_.size_leaf_vector > 1split_typecategories_segmentscategories_sizescategories_nodesUnknown Model Builder:dot tree dump GraphvizParamTreeParamtree_paramnum_nodes Line , around ^`/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/json.h, Expect '"' but reach end of line ch == '\"'Error at, Expect '"' but get 'unknown string escape \ch == ','ch == ':', Expect ':' but get ', JSON object expect '}' or ',' 'Check failed: is_numerical in feature map is categorical but tree node is numerical.Check failed: is_categoricalUnknown feature map type. in feature map is numerical but tree node is categorical.mϷpos != std::string::nposparam_.num_nodes < std::numeric_limits::max()number of nodes in the tree exceed 2^31ch == '{', Expect '{' but get 'j_end - j_begin > 0std::numeric_limits::min() != max_catn_nodes != 0sum_hessian.size() == n_nodeslefts.size() == n_nodesrights.size() == n_nodesparents.size() == n_nodesindices.size() == n_nodesconds.size() == n_nodesloss_changes.size() == n_nodesbase_weights.size() == n_nodesdefault_left.size() == n_nodesyes_color#0000FFno_color#FF0000rankdircondition_node_paramsleaf_node_paramsLeaf node configurationgraph_attrsEdge color when meets the node condition.Edge color when doesn't meet the node condition.Passed to graphiz via graph_attr.Conditional node configurationAny other extra attributes for graphviz `graph_attr`.learning_ratemin_split_lossmax_depthmax_leavesgrow_policydepthwiselossguidemax_cat_to_onehotmax_cat_thresholdmin_child_weightreg_lambdareg_alphasubsamplesampling_methodgradient_basedcolsample_bynodecolsample_bylevelcolsample_bytreesketch_ratiocache_optrefresh_leafmonotone_constraintsinteraction_constraintssparse_thresholdetaLearning rate(step size) of update.Minimum loss reduction required to make a further partition.Maximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policyMaximum number of leaves; 0 indicates no limit.if using histogram-based algorithm, maximum number of bins per featureTree 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)Maximum number of categories to use one-hot encoding based split.Maximum number of categories considered for split. Used only by partition-basedsplits.Minimum sum of instance weight(hessian) needed in a child.L2 regularization on leaf weightL1 regularization on leaf weightMaximum delta step we allow each tree's weight estimate to be. If the value is set to 0, it means there is no constraintRow subsample ratio of training instance.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)Subsample ratio of columns, resample on each node (split).Subsample ratio of columns, resample on each level.Subsample ratio of columns, resample on each tree construction.EXP Param: Sketch accuracy related parameter of approximate algorithm.EXP Param: Cache aware optimization.Whether the refresh updater needs to update leaf values.Constraint of variable monotonicityConstraints 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 informationpercentage threshold for treating a feature as sparse, "gain": {loss_chg}, "cover": {sum_hess}{tabs}{nid}{cond}{left}{missing}{tabs}{nid}:[{fname}<{cond}] yes={left},no={right},missing={missing}{tabs}{nid}:[{fname}:{cond}] yes={right},no={left},missing={missing} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {left}, "no": {right}, "missing": {missing} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {right}, "no": {left}, "missing": {missing} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "yes": {yes}, "no": {no}{yes}{no}{{properties} {stat}, "children": [{left}, {right} {indent}]}{properties}{stat}{indent}{parent} {left} {right}{parent}{parent}{stat} {left} {right},gain={loss_chg},cover={sum_hess}digraph { graph [ rankdir={rankdir} ] {graph_attrs} {nodes}}{newline}{indent}{nodes}{nid}:[{fname}] yes={yes},no={no}, missingnoyes{color}{branch} {nid} -> {child} [label="{branch}" color="{color}"] {<}{params} {nid} [ label="{fname}{<}{cond}" {params}] { "nodeid": {nid}, "leaf": {leaf} {stat}}, "cover": {sum_hess} {leaf}{sum_hess} {nid} [ label="{fname}:{cond}" {params}] {tabs}{nid}:leaf={leaf}{stats},cover={cover}{nodes} {nid} [ label="leaf={leaf-value}" {params}] limit >= 2..., {leaf-value}" edge graph [ {key}="{value}" ] The following parameters for graphviz are not recognized: Failed to parse graphviz parameters: N7xgboost7RegTreeEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryISt6vectorIiSaIiEEEES5_EEN4dmlc9parameter10FieldEntryISt6vectorIiSaIiEEEEN7xgboost13TreeGeneratorEN7xgboost13TextGeneratorEN7xgboost13JsonGeneratorEN7xgboost17GraphvizGeneratorE*N7xgboostUlRKNS_10FeatureMapERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE_E*N7xgboostUlRKNS_10FeatureMapERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE0_E*N7xgboostUlRKNS_10FeatureMapENSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE1_ENumber of features used in tree size_leaf_vectorSize of leaf vector, reserved fo?Unknown tree updater /__w/ml-builds/ml-builds/xgboost/src/tree/tree_updater.ccTree constructor that uses approximate histogram construction for each node./__w/ml-builds/ml-builds/xgboost/src/tree/../data/../common/io.h/__w/ml-builds/ml-builds/xgboost/src/tree/hist/evaluate_splits.hpartition > 0/__w/ml-builds/ml-builds/xgboost/src/tree/../common/hist_util.hid != kMax/__w/ml-builds/ml-builds/xgboost/src/tree/../common/row_set.helem_of_each_node_.size() == 0Ui < first_dimension_.size()/__w/ml-builds/ml-builds/xgboost/src/tree/hist/sampler.hexponent <= mod/__w/ml-builds/ml-builds/xgboost/src/tree/../common/partition_builder.hCheck failed: tree.IsLeaf(node.node_id)ptr_offset <= row_set.Data()->size()i < ranges_.size()end > beginnid < nodes_begin < endn_left == 0n_right == 0n_left + n_right == e.Size()begin + n_left <= e.endbegin + n_left + n_right == e.endtid < nthreads_/__w/ml-builds/ml-builds/xgboost/src/tree/../data/../common/ref_resource_view.hnidx != kRootvector::_M_fill_insertcut_ptr[fidx] <= static_cast(std::numeric_limits::max())cut_ptr[fidx + 1] <= static_cast(std::numeric_limits::max())/__w/ml-builds/ml-builds/xgboost/src/tree/../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/tree/hist/histogram.hCheck failed: !nodes_to_build.empty()Check failed: out_preds.Device().IsCPU()part.Size() == n_nodesout_preds.Size() > 0UCheck failed: p_last_treeout_preds.Shape(1) == n_targetsUpdatePredictionCache/__w/ml-builds/ml-builds/xgboost/src/tree/updater_approx.ccout_preds.Size() == data->Info().num_row_/__w/ml-builds/ml-builds/xgboost/src/tree/common_row_partitioner.hupper_bound < static_cast(std::numeric_limits::max())p_tree->LeftChild(nidx) + 1 == p_tree->RightChild(nidx)hist_train_paramnodes == targeted_hists.size()row_ptr_[nid] == kMaxcurrent_size_ == new_size/__w/ml-builds/ml-builds/xgboost/src/tree/hist/hist_cache.hCheck failed: p_nodes_to_buildCheck failed: !this->hist_.HasExceeded()Check failed: p_nodes_to_subnodes_to_build.size() >= nodes_to_sub.size()nodes_to_sub.size() + nodes_to_build.size() == valid_candidates.size() * 2gpair.Shape(1) == p_tree->NumTargets()t_gpair.Shape(0) == p_fmat->Info().num_row_Check failed: gpair.Contiguous()gpair.Shape(1) == n_targetsp_fmat->Info().num_row_ == gpair.Shape(0)target_builders_.size() == n_targetsCheck failed: dummy_sub.empty()loss_chgsindexsplit_valuecat_bitsis_catleft_sumright_sumall_serialized.size() >= local_entries.size()Check failed: !features.empty()InitRoot/__w/ml-builds/ml-builds/xgboost/src/tree/hist/../../common/transform.hInitDatan_targets >= 1n_total_bins == page.cut.TotalBins()gidx > -1any_missing == truedecision_storage_.size() == decision.NumValues()base_rowid == gmat.base_rowidBuildHistogramEvaluateSplitsLeafPartitionCheck failed: hist_param_.GetInitialised()/__w/ml-builds/ml-builds/xgboost/src/tree/hist/../split_evaluator.hp.monotone_constraints.size() <= n_featuresThe size of monotone constraint should be less or equal to the number of features./__w/ml-builds/ml-builds/xgboost/src/tree/../collective/../data/../common/common.hCheck failed: out.Contiguous()param.sampling_method == TrainParam::kUniformOnly uniform sampling is supported, gradient-based sampling is only support by GPU Hist.FbRKN7xgboost4tree14CPUExpandEntryES3_EN7xgboost11TreeUpdaterEN7xgboost4tree19GlobalApproxUpdaterE*N7xgboost4treeUlPKNS_7ContextEPKNS_7ObjInfoEE_EPFbRKN7xgboost4tree14CPUExpandEntryES3_EN7xgboost6common6ColumnIhEEN7xgboost6common16SparseColumnIterIhEESt23_Sp_counted_ptr_inplaceIN7xgboost6common13ColumnSamplerESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEN7xgboost6common6ColumnItEEN7xgboost6common15DenseColumnIterItLb1EEEN7xgboost6common16SparseColumnIterItEEN7xgboost6common6ColumnIjEEN7xgboost6common15DenseColumnIterIjLb1EEEN7xgboost6common16SparseColumnIterIjEESt15_Sp_counted_ptrIPN7xgboost6common16PartitionBuilderILm2048EE9BlockInfoELN9__gnu_cxx12_Lock_policyE2EEGlobalApproxUpdahist_train_paramctx_opt_dense_coldefault_directionlearnrightEXP Param: speed optimization for dense column.Default direction choice when encountering a missing valuefmat.Info().num_row_ == position_.size()param_.sampling_method == TrainParam::kUniformOnly uniform sampling is supported, gradient-based sampling is only support by GPU Hist./__w/ml-builds/ml-builds/xgboost/src/tree/../common/../collective/../data/../common/common.hparam_.max_depth > 0exact tree method doesn't support unlimited depth./__w/ml-builds/ml-builds/xgboost/src/tree/../common/transform.hUpdater `grow_colmaker` or `exact` tree method doesn't support distributed training.Updater `grow_colmaker` or `exact` tree method doesn't support external memory training.Updater `grow_colmaker` or `exact` tree methodcolumn sample by node is not yet supported by the exact tree method/__w/ml-builds/ml-builds/xgboost/src/tree/split_evaluator.hgpair->Shape(1) == 1N7xgboost4tree8ColMaker7BuilderEN7xgboost4tree8ColMakerE*N7xgboost4treeUlPKNS_7ContextET_E_Ecolmaker_train_pPruner that prune the tree according to statistics./__w/ml-builds/ml-builds/xgboost/src/tree/updater_prune.ccCheck failed: tree[nid].IsLeaf()Check failed: !tree[pid].IsLeaf()nid >= 1tree pruning end, extra nodes, pruned nodes, max_depth=N7xgboost4tree10TreePrunerE*N7xgboost4treeUlPKNS_7ContextEPKNS_7ObjInfoEE_E/src/tree/updateGrow tree using quantized histogram.Check failed: p_tree->IsMultiTarget()left_child > candidate.nidright_child > candidate.nidstats_.Shape(1) == n_targets/__w/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.ccout_preds.Size() == data->Info().num_row_ * p_last_tree_->NumTargets()Check failed: p_mtimpl_Check failed: p_impl_root_sum_tloc.Shape(1) == gpair.Shape(1)Check failed: root_sum.CContiguous()row_ptr.size() >= 2UpdateTreeUpdatePositionp_tree->LeftChild(candidate.nid) > candidate.nidCheck failed: param->monotone_constraints.empty()monotone constraintMultiTargetHistBuilderHistUpdaterFbRKN7xgboost4tree16MultiExpandEntryES3_EN7xgboost4tree17QuantileHistMakerE*N7xgboost4treeUlPKNS_7ContextEPKNS_7ObjInfoEE_EN7xgboost6common15DenseColumnIterIhLb1EEEPFbRKN7xgboost4tree16MultiExpandEntryES3_EN7xgboost6common15DenseColumnIterIhLb0EEEN7xgboost6common15DenseColumnIterItLb0EEEN7xgboost6common15DenseColumnIterIjLb0EEErefresh/__w/ml-builds/ml-builds/xgboost/src/tree/updater_refresh.ccbatch.Size() < std::numeric_limits::max()Refresher that refreshes the weight and statistics according to data.N7xgboost4tree13TreeRefresherE*N7xgboost4treeUlPKNS_7ContextET_E_E/__w/ml-builds/ml-builds/xgboost/src/tree/../common/io.hsyncSyncher that synchronize the tree in all distributed nodes.N7xgboost4tree11TreeSyncherE*N7xgboost4treeUlPKNS_7ContextET_E_E/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.hLibSVMParserParamLibFMParserParamCSVParserParamCheck failed: TryLoadCache()failed to build cache file finish reading at .split.partname_cache.size() == 1Uname_args.size() == 1U/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/uri_spec.honly one `#` is allowed in file path for cachefile specificationlibsvmUnknown data type /__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data.cc/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/threadediter.hCheck failed: out_data_ != NULLCalling Value at beginning or end?/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.hcannot call ParseNext/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./././strtonum.hCheck failed: base <= 10 && base >= 2sign == true/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././parameter.hFile formatindexing_modeIf >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.libfmIf >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.csvFile format.label_columndelimiterweight_columnColumn index (0-based) that will put into label.Delimiter used in the csv file.Column index that will put into instance weights./__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./row_block.hlabel.size() + 1 == offset.size()Check failed: offset.back() == value.size() || value.size() == 0offset.back() == index.size()No threadparam_.format == "csv"/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/csv_parser.hCheck failed: param_.label_column != param_.weight_column || param_.label_column < 0Must have distinct columns for labels and instance weightsCheck failed: producer_sig_.load(std::memory_order_acquire) == kDestroyCheck failed: cell != __null || produce_end_.load(std::memory_order_acquire)Check failed: producer_sig_.load(std::memory_order_acquire) != kDestroy/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/libfm_parser.hparam_.format == "libfm"/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.hparam_.format == "libsvm"Check failed: fi->Read(&label)Check failed: fi->Read(&weight)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))Bad RowBlock formatCheck failed: fi->Read(&qid)MB read,finish reading at %g MB/sec/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/disk_row_iter.hCheck failed: !producer_sig_processed_.load(std::memory_order_acquire)Check failed: producer_sig_.load(std::memory_order_acquire) == kProduceMake sure you call BeforeFirst not inconcurrent with Next!Check failed: produce_end_.load(std::memory_order_acquire)Delimiter '' is not found in the line. Expected '' as the delimiter to separate fields.Check failed: out->label.size() == 0 || out->label.size() + 1 == out->offset.size()Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size()Check failed: out->field.size() == out->index.size()Check failed: out->label.size() + 1 == out->offset.size()qid:/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/././text_parser.hchunk.size != 0UNSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS4_17RowBlockContainerImlEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_EEEEEEN4dmlc12ScopedThreadEN4dmlc8DataIterINS_8RowBlockIjfEEEEN4dmlc12RowBlockIterIjfEEN4dmlc8DataIterINS_8RowBlockImfEEEEN4dmlc12RowBlockIterImfEEN4dmlc8DataIterINS_8RowBlockIjiEEEEN4dmlc12RowBlockIterIjiEEN4dmlc8DataIterINS_8RowBlockImiEEEEN4dmlc12RowBlockIterImiEEN4dmlc8DataIterINS_8RowBlockIjlEEEEN4dmlc12RowBlockIterIjlEEN4dmlc8DataIterINS_8RowBlockImlEEEEN4dmlc12RowBlockIterImlEEN4dmlc6ParserIjfEEN4dmlc6ParserImfEEN4dmlc6ParserIjiEEN4dmlc6ParserImiEEN4dmlc6ParserIjlEEN4dmlc6ParserImlEEN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEEN4dmlc4data11DiskRowIterIjfEEN4dmlc4data12BasicRowIterIjfEEN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEEN4dmlc4data11DiskRowIterImfEEN4dmlc4data12BasicRowIterImfEEN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEEN4dmlc4data11DiskRowIterIjiEEN4dmlc4data12BasicRowIterIjiEEN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEEN4dmlc4data11DiskRowIterImiEEN4dmlc4data12BasicRowIterImiEEN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEEN4dmlc4data11DiskRowIterIjlEEN4dmlc4data12BasicRowIterIjlEEN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEEN4dmlc4data11DiskRowIterImlEEN4dmlc4data12BasicRowIterImlEEN4dmlc4data10ParserImplIjfEEN4dmlc4data14TextParserBaseIjfEEN4dmlc4data12LibSVMParserIjfEEN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEEN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEEN4dmlc4data14ThreadedParserIjfEEN4dmlc4data10ParserImplImfEEN4dmlc4data14TextParserBaseImfEEN4dmlc4data12LibSVMParserImfEEN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEEN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEEN4dmlc4data14ThreadedParserImfEEN4dmlc4data11LibFMParserIjfEEN4dmlc4data11LibFMParserImfEEN4dmlc4data9CSVParserIjfEEN4dmlc4data9CSVParserImfEEN4dmlc4data10ParserImplIjiEEN4dmlc4data14TextParserBaseIjiEEN4dmlc4data9CSVParserIjiEEN4dmlc4data10ParserImplImiEEN4dmlc4data14TextParserBaseImiEEN4dmlc4data9CSVParserImiEEN4dmlc4data10ParserImplIjlEEN4dmlc4data14TextParserBaseIjlEEN4dmlc4data9CSVParserIjlEEN4dmlc4data10ParserImplImlEEN4dmlc4data14TextParserBaseImlEEN4dmlc4data9CSVParserImlEEZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlPPSt6vectorINS0_17RowBlockContainerIjfEESaIS8_EEE_ZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlvE0_ZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlPPSt6vectorINS0_17RowBlockContainerImfEESaIS8_EEE_ZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlvE0_ZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjfEEE_ZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImfEEE_ZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjiEEE_ZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImiEEE_ZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjlEEE_ZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImlEEE_ZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlvE0_NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterISt6vectorINS3_4data17RowBlockContainerIjfEESaIS8_EEE4InitESt8functionIFbPPSA_EESC_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterISt6vectorINS3_4data17RowBlockContainerImfEESaIS8_EEE4InitESt8functionIFbPPSA_EESC_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjfEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImfEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjiEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImiEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjlEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImlEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEEhdfs://viewfs://s3://http://https://azure://unknown filesystem protocol stdinCheck failed: fp_ != NULLCheck failed: part < nsplitindexed_recordiounknown input split type rbBeforeFirst is not supported/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/cached_input_split.hResetPartition is not supported in CachedInputSplit/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/single_file_split.hCheck failed: part_index == 0 && num_parts == 1InputSplit do not support write/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io.ccPlease compile with DMLC_USE_HDFS=1 to use hdfsPlease compile with DMLC_USE_S3=1 to use S3Please compile with DMLC_USE_AZURE=1 to use AzureSingleFileSplit: fail to open invalid input parameter for InputSplit::Createneed to pass index file to use IndexedRecordIOCheck failed: nread == sizeof(size) has invalid cache file formatCheck failed: fi_->Read(p->begin, size) == sizeCheck failed: this->InitCachedIter()Failed to initialize CachedIterFvvEN4dmlc10InputSplitEN4dmlc2io15SingleFileSplitEN4dmlc8DataIterINS_2io14InputSplitBase5ChunkEEEN4dmlc12ThreadedIterINS_2io14InputSplitBase5ChunkEEEN4dmlc2io16CachedInputSplitEN4dmlc2io18ThreadedInputSplitEZN4dmlc2io16CachedInputSplit15InitPreprocIterEvEUlPPNS0_14InputSplitBase5ChunkEE_PFvvEZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlPPNS0_14InputSplitBase5ChunkEE_ZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlvE0_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlPPNS2_5ChunkEE_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlvE0_NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_2io14InputSplitBase5ChunkEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEE /__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.ccCheck failed: begin != endN4dmlc2io12LineSplitterE/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/recordio_split.ccCheck failed: fi->Read(&lrec, sizeof(lrec)) != 0(reinterpret_cast(begin) & 3UL) == 0U(reinterpret_cast(end) & 3UL) == 0UCheck failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->end(reinterpret_cast(chunk->begin) & 3UL) == 0U(reinterpret_cast(chunk->end) & 3UL) == 0UCheck failed: chunk->begin <= chunk->endCheck failed: p[0] == RecordIOWriter::kMagicinvalid record io formatCheck failed: p >= pbegin + 2Invalid RecordIO FormatCheck failed: cflag == 1UN4dmlc2io16RecordIOSplitterE/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.ccIndexedRecordIOSplitter does not support multiple index filesexpanded_list.size() == 1ulN4dmlc2io23IndexedRecordIOSplitterE/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/input_split_base.ccCheck failed: offset_end_ >file_offset_[file_ptr_end_]Check failed: file_ptr_end_ < files_.size()file offset not calculated correctlyThis could due to compiler version, g++-4.9 is neededCannot find any files that matches the URI pattern Check failed: files_[i].size % align_bytes == 0curr=,begin=,end=,fileptr=,fileoffset=offset[]= bad regex files_.size() != 0Ufile do not align by bytesN4dmlc2io14InputSplitBaseELocalFileSystem.GetPathInfo: stdoutCheck failed: allow_null LocalFileSystem::Open "": ../__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/local_filesys.ccLocalFileSystem.GetPathInfo: detected symlink LocalFileSystem.ListDirectory Check failed: !std::fseek(fp_, static_cast(pos), SEEK_SET)Check failed: std::fwrite(ptr, 1, size, fp_) == sizeFileStream.Write incompleteN4dmlc2io15LocalFileSystemEN4dmlc2io10FileStreamElstat(path.c_str(), &sb) == 0Couldn't remove file ~TemporaryDirectory(): /__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/filesystem.hdmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/filesys.ccCheck failed: !IsSymlink(info.path.name)Symlink not supported in TemporaryDirectorySuccessfully deleted temporary directory Could not remove temporary directory N4dmlc2io10FileSystemE;<6& tX6Ht6t6uA#uiFuu4Lu̖uduu@u 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