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gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSN4dmlc8DataIterINS_8RowBlockIjfEEEE_ZTIN4dmlc8DataIterINS_8RowBlockIjfEEEE_ZTSN4dmlc12RowBlockIterIjfEE_ZTIN4dmlc12RowBlockIterIjfEE_ZTSN4dmlc8DataIterINS_8RowBlockImfEEEE_ZTIN4dmlc8DataIterINS_8RowBlockImfEEEE_ZTSN4dmlc12RowBlockIterImfEE_ZTIN4dmlc12RowBlockIterImfEE_ZTSN4dmlc8DataIterINS_8RowBlockIjiEEEE_ZTIN4dmlc8DataIterINS_8RowBlockIjiEEEE_ZTSN4dmlc12RowBlockIterIjiEE_ZTIN4dmlc12RowBlockIterIjiEE_ZTSN4dmlc8DataIterINS_8RowBlockImiEEEE_ZTIN4dmlc8DataIterINS_8RowBlockImiEEEE_ZTSN4dmlc12RowBlockIterImiEE_ZTIN4dmlc12RowBlockIterImiEE_ZTSN4dmlc8DataIterINS_8RowBlockIjlEEEE_ZTIN4dmlc8DataIterINS_8RowBlockIjlEEEE_ZTSN4dmlc12RowBlockIterIjlEE_ZTIN4dmlc12RowBlockIterIjlEE_ZTSN4dmlc8DataIterINS_8RowBlockImlEEEE_ZTIN4dmlc8DataIterINS_8RowBlockImlEEEE_ZTSN4dmlc12RowBlockIterImlEE_ZTIN4dmlc12RowBlockIterImlEE_ZTSN4dmlc6ParserIjfEE_ZTIN4dmlc6ParserIjfEE_ZTSN4dmlc6ParserImfEE_ZTIN4dmlc6ParserImfEE_ZTSN4dmlc6ParserIjiEE_ZTIN4dmlc6ParserIjiEE_ZTSN4dmlc6ParserImiEE_ZTIN4dmlc6ParserImiEE_ZTSN4dmlc6ParserIjlEE_ZTIN4dmlc6ParserIjlEE_ZTSN4dmlc6ParserImlEE_ZTIN4dmlc6ParserImlEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEE_ZTSN4dmlc4data11DiskRowIterIjfEE_ZTIN4dmlc4data11DiskRowIterIjfEE_ZTSN4dmlc4data12BasicRowIterIjfEE_ZTIN4dmlc4data12BasicRowIterIjfEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEE_ZTSN4dmlc4data11DiskRowIterImfEE_ZTIN4dmlc4data11DiskRowIterImfEE_ZTSN4dmlc4data12BasicRowIterImfEE_ZTIN4dmlc4data12BasicRowIterImfEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEE_ZTSN4dmlc4data11DiskRowIterIjiEE_ZTIN4dmlc4data11DiskRowIterIjiEE_ZTSN4dmlc4data12BasicRowIterIjiEE_ZTIN4dmlc4data12BasicRowIterIjiEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEE_ZTSN4dmlc4data11DiskRowIterImiEE_ZTIN4dmlc4data11DiskRowIterImiEE_ZTSN4dmlc4data12BasicRowIterImiEE_ZTIN4dmlc4data12BasicRowIterImiEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEE_ZTSN4dmlc4data11DiskRowIterIjlEE_ZTIN4dmlc4data11DiskRowIterIjlEE_ZTSN4dmlc4data12BasicRowIterIjlEE_ZTIN4dmlc4data12BasicRowIterIjlEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEE_ZTSN4dmlc4data11DiskRowIterImlEE_ZTIN4dmlc4data11DiskRowIterImlEE_ZTSN4dmlc4data12BasicRowIterImlEE_ZTIN4dmlc4data12BasicRowIterImlEE_ZTSN4dmlc4data10ParserImplIjfEE_ZTIN4dmlc4data10ParserImplIjfEE_ZTSN4dmlc4data14TextParserBaseIjfEE_ZTIN4dmlc4data14TextParserBaseIjfEE_ZTSN4dmlc4data12LibSVMParserIjfEE_ZTIN4dmlc4data12LibSVMParserIjfEE_ZTSN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTIN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTSN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTIN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTSN4dmlc4data14ThreadedParserIjfEE_ZTIN4dmlc4data14ThreadedParserIjfEE_ZTSN4dmlc4data10ParserImplImfEE_ZTIN4dmlc4data10ParserImplImfEE_ZTSN4dmlc4data14TextParserBaseImfEE_ZTIN4dmlc4data14TextParserBaseImfEE_ZTSN4dmlc4data12LibSVMParserImfEE_ZTIN4dmlc4data12LibSVMParserImfEE_ZTSN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTIN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTSN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTIN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTSN4dmlc4data14ThreadedParserImfEE_ZTIN4dmlc4data14ThreadedParserImfEE_ZTSN4dmlc4data11LibFMParserIjfEE_ZTIN4dmlc4data11LibFMParserIjfEE_ZTSN4dmlc4data11LibFMParserImfEE_ZTIN4dmlc4data11LibFMParserImfEE_ZTSN4dmlc4data9CSVParserIjfEE_ZTIN4dmlc4data9CSVParserIjfEE_ZTSN4dmlc4data9CSVParserImfEE_ZTIN4dmlc4data9CSVParserImfEE_ZTSN4dmlc4data10ParserImplIjiEE_ZTIN4dmlc4data10ParserImplIjiEE_ZTSN4dmlc4data14TextParserBaseIjiEE_ZTIN4dmlc4data14TextParserBaseIjiEE_ZTSN4dmlc4data9CSVParserIjiEE_ZTIN4dmlc4data9CSVParserIjiEE_ZTSN4dmlc4data10ParserImplImiEE_ZTIN4dmlc4data10ParserImplImiEE_ZTSN4dmlc4data14TextParserBaseImiEE_ZTIN4dmlc4data14TextParserBaseImiEE_ZTSN4dmlc4data9CSVParserImiEE_ZTIN4dmlc4data9CSVParserImiEE_ZTSN4dmlc4data10ParserImplIjlEE_ZTIN4dmlc4data10ParserImplIjlEE_ZTSN4dmlc4data14TextParserBaseIjlEE_ZTIN4dmlc4data14TextParserBaseIjlEE_ZTSN4dmlc4data9CSVParserIjlEE_ZTIN4dmlc4data9CSVParserIjlEE_ZTSN4dmlc4data10ParserImplImlEE_ZTIN4dmlc4data10ParserImplImlEE_ZTSN4dmlc4data14TextParserBaseImlEE_ZTIN4dmlc4data14TextParserBaseImlEE_ZTSN4dmlc4data9CSVParserImlEE_ZTIN4dmlc4data9CSVParserImlEE_ZTSZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlPPSt6vectorINS0_17RowBlockContainerIjfEESaIS8_EEE__ZTSZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlvE0__ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS2_4data17RowBlockContainerIjfEESaIS7_EEE4InitESt8functionIFbPPS9_EESB_IFvvEEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS2_4data17RowBlockContainerIjfEESaIS7_EEE4InitESt8functionIFbPPS9_EESB_IFvvEEEUlvE_vEEEE_ZTSZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlPPSt6vectorINS0_17RowBlockContainerImfEESaIS8_EEE__ZTSZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlvE0__ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS2_4data17RowBlockContainerImfEESaIS7_EEE4InitESt8functionIFbPPS9_EESB_IFvvEEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS2_4data17RowBlockContainerImfEESaIS7_EEE4InitESt8functionIFbPPS9_EESB_IFvvEEEUlvE_vEEEE_ZTSZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjfEEE__ZTSZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlvE0__ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjfEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjfEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTSZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImfEEE__ZTSZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlvE0__ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerImfEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerImfEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTSZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjiEEE__ZTSZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlvE0__ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjiEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjiEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTSZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImiEEE__ZTSZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlvE0__ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerImiEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerImiEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTSZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjlEEE__ZTSZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlvE0__ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjlEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjlEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTSZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImlEEE__ZTSZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlvE0__ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerImlEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerImlEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS3_4data17RowBlockContainerIjfEESaIS8_EEE4InitESt8functionIFbPPSA_EESC_IFvvEEEUlvE_vEEE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ְG"? ְGB? ְGb? ְG? ְG? ְG? ְG? @ @"  @B @b @ @ @ @ "@ &@" *@B .@b 2@ 6@ :@ >@ B@ F@" J@B N@b R@ V@ Z@ ^@ b@ f@" j@B n@b r@ v@ z@ ~@ @ @" @B @b @ @ @ @ @ @" @B @b @ @ @ @ @ @" @B @b @ @ @ @ @ @" @B @b @ @ @ @ A A"  AB Ab A A A A ְ"A ְ&A" ְ*AB ְ.Ab ְ2A ְ6A ְ:A ְ>A ְBA ְFA" ְJAB ְNAb ְRA ְVA ְZA ְ^A ְbA ְfA" ְjAB ְnAb ְrA ְvA ְzA ְ~A ְA ְA" ְAB ְAb ְA ְA ְA ְA ְA ְA" ְAB ְAb ְA ְA ְA ְA ְA ְA" ְAB ְAb ְA ְA ְA ְA ְA ְA" ְAB ְAb ְA ְA ְA ְA ְB ְB" ְ BB ְBb ְB ְB ְB ְB ְ"B ְ&B" ְ*BB ְ.Bb ְ2B ְ6B ְ:B ְ>B ְBB ְFB" ְJBB ְNBb ְRB ְVB ְZB ְ^B ְbB ְfB" ְjBB ְnBb ְrB ְvB ְzB ְ~B ְB ְB" ְBB ְBb ְB ְB ְB ְB ְB ְB" ְBB ְBb ְB ְB ְB ְB ְB ְB" ְBB ְBb ְB ְB ְB ְB ְB ְB" ְBB ְBb ְB ְB ְB ְB ְC ְC" ְ CB ְCb ְC ְC ְC ְC ְ"C ְ&C" ְ*CB ְ.Cb ְ2C ְ6C ְ:C ְ>C ְBC ְFC" ְJCB ְNCb ְRC ְVC ְZC ְ^C ְbC ְfC" ְjCB ְnCb ְrC ְvC ְzC ְ~C ְC ְC" ְCB ְCb ְC ְC ְC ְC ְC ְC" ְCB ְCb ְC ְC ְC ְC ְC ְC" ְCB ְCb ְC ְC ְC ְC ְC ְC" ְCB ְCb ְC ְC ְC ְC ְD ְD" ְ DB ְDb ְD ְD ְD ְD ְ"D! ְ&D"! ְ*DB! ְ.Db! ְ2D! ְ6D! ְ:D! ְ>D! ְBD" ְFD"" ְJDB" ְNDb" ְRD" ְVD" ְZD" ְ^D" ְbD# ְfD"# ְjDB# ְnDb# ְrD# ְvD# ְzD# ְ~D# ְD$ ְD"$ ְDB$ ְDb$ ְD$ ְD$ ְD$ ְD$ ְD% ְD"% ְDB% ְDb% ְD% ְD% ְD% ְD% ְD& ְD"& ְDB& ְDb& ְD& ְD& ְD& ְD& ְD' ְD"' ְDB' ְDb' ְD' ְD' ְD' ְD' ְE( ְE"( ְ EB( ְEb( ְE( ְE( ְE( ְE( ְ"E) ְ&E") ְ*EB) ְ.Eb) ְ2E) ְ6E) ְ:E) ְ>E) ְBE* ְFE"* ְJEB* ְNEb* ְRE* ְVE* ְZE* ְ^E* ְbE+ ְfE"+ ְjEB+ ְnEb+ ְrE+ ְvE+ ְzE+ ְ~E+ ְE, ְE", ְEB, ְEb, ְE, ְE, ְE, ְE, ְE- ְE"- ְEB- ְEb- ְE- ְE- ְE- ְE- ְE. ְE". ְEB. ְEb. ְE. ְE. ְE. ְE. ְE/ ְE"/ ְEB/ ְEb/ ְE/ ְE/ ְE/ ְE/ ְF0 ְF"0 ְ FB0 ְFb0 ְF0 ְF0 ְF0 ְF0 ְ"F1 ְ&F"1 ְ*FB1 ְ.Fb1 ְ2F1 ְ6F1 ְ:F1 ְ>F1 ְBF2 ְFF"2 ְJFB2 ְNFb2 ְRF2 ְVF2 ְZF2 ְ^F2 ְbF3 ְfF"3 ְjFB3 ְnFb3 ְrF3 ְvF3 ְzF3 ְ~F3 ְF4 ְF"4 ְFB4 ְFb4 ְF4 ְF4 ְF4 ְF4 ְF5 ְF"5 ְFB5 ְFb5 ְF5 ְF5 ְF5 ְF5 ְF6 ְF"6 ְFB6 ְFb6 ְF6 ְF6 ְF6 ְF6 ְF7 ְF"7 ְFB7 ְFb7 ְF7 ְF7 ְF7 ְF7 ְG8 ְG"8 ְ GB8 ְGb8 ְG8 ְG8 ְG8 ְG8 ְ"G9 ְ&G"9 ְ*GB9 ְ.Gb9 ְ2G9 ְ6G9 ְ:G9 ְ>G9 ְBG: ְFG": ְJGB: ְNGb: ְRG: ְVG: ְZG: ְ^G: ְbG; ְfG"; ְjGB; ְnGb; ְrG; ְvG; ְzG; ְ~G; ְG< ְG"< ְGB< ְGb< ְG< ְG< ְG< ְG< ְG= ְG"= ְGB= ְGb= ְG= ְG= ְG= ְG= ְG> ְG"> ְGB> ְGb> ְG> ְG> ְG> ְG> ְG? 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T@.8~ ՠ;@@5@@95SKT`"@aB@T݁`@a@T؁ A@TӁsT[@t́?@@!@@TƁ?@@!@T?@@!@@TE7A@ @FSA[BcCkDsE{ƨC_ִ!/"҃Gҵ#W@@) /"R!|)wG̈́G!`/BȄЀG!" ÄG!/"ҾGRc!B!`@!`!Ҭ;@@!!@@CR"ң#9yM[@/t[@@!/"҃GҵW#(@@) /"R!һ{vGqG!`/BlЀG!" gG!/"bGR!B!`[@!"U;@@Q@CR"ң9K&#g@sg@@@99v?@>Ss##( T$TBt%?h48t[|[?@T@."} ՟>WH T!T B?h48t]|]?@T@. }>g T T ?h48Rc_d_@0)5A (@q TAq T@I~5@B@T@@T@B@T Tt@Bs|Y@T>S)TwS@YsS@@ iW@KsW@@ [g@=sg@@ bR!x!!!`Bҍ!b҈#AqTXcs{g@R!x!n!ig@"@!@d!B!`_!`ZClg@4 A@TJ`!/"҃GEOW /"R'@)%@!yzuG/ЀG!`/B*G!" %ЀG!/" G!RŌ!B!`@!@[!Ђ!@ @SCR"ңS9"@99@9@#9@9#98@9#9Iu?@@`J@`R#Ҵ7@?@z|H բ@_`T@BT #܎b|u@_CR"ң_9?@@!@_`Tq?@@!@Tk?@@!@ Te@[CR"ң[9@WCR"ңW9Cg@ A@TF O{cSO[#Ekb@scG=K=O=S=3tҿt@l@@V@CXF@W$@FcY$$@#s$@_@#T@u`#@bC@T~`@b@T~@A@T~{T"CTbT_`T`"@aB@T~`@a@T~ A@T~sT`T"@B@T~@@T~ A@T~T@@@"T`@~T@~@@^TO@uB@u@@aNT@.z>HVTXTVt&h48@s@? TGB?F@c @`?֠@@aB`"@T@Tn~`@a@Ti~`A@Te~@_P T@@@AT@.zOPT"@B@TM~@@TH~ A@TC~T@w<~@@aTW@@W# T@v`"@aB@T+~`@a@T&~ A@T!~sT"HT_@T?`T`"@aB@T~`@a@T ~ A@T~s?T`T"@B@T}@@T} A@T}T@@@"T`@}T@}EA@ NSA[BcCkDsE{ƨ_@T}`@a@T}`A@T}@}@ @^>O#KC_T"T0?h38[[?@T@.y >cT TB?h38]]?@T@.y>gTT3?h38__qT@`(TSzB@z@``@T@.y>T Tv&h68BA`ja2@s@B@T\}@@TW}@@TS}T@Y@@T>_ITG@6_@p_@@>wTTvv{h68`@{@?@T@.py >{T@TvaBh68`@a"@_@!T@.Zy աO@c@oc@@e աK@g@og@@?h38__qT@@TzB@z@``@aT@.&y >sTTVv&h68@sl >kTTv{h68`@{@?@T@.y >oH TT vaBh68`@a"@_@aT@.x @9@9@9c9@99 C@҄{@`afo{@`@lww@`a Yow@`@I ա?@j@`"a*Lo@`"@@9bB9a@9aB94@9a9FcRo@`a4oo@`@CEk@`a 'ok@`@ ա8s@`"a*os@`"@j|na@9aB9p@9a9@9bB9Z3@6>WT T4O@vth48`4@v7@?@T@.[x>[TTO@aBth48`T$@a"W @_@!T@.Ex[@`an[@`@݉W@`a nW@`@;@щ@`"a*n@`"@H@9`B9@9bB9@@9`9?뀢T`"@aB@T{`@a@T{ A@T{sT@sRSS@3@O@@";@3@$qN @BT{ բ@_T{`@_@T{ex `@@T{ `@@Tw{a@To{;@pq{kspBc$@S#[@TC T@v`"@aB@TO{`@a@TJ{s A@TD{T"HTT`T"@B@T6{@@T1{ A@T+{_T?`T"@B@T"{@@T{ AT{?T`@t'@s@"T`@ {T`@SA[BcCkDsE{ƨ{T"@B@Tz@@Tz A@Tz?T`@@SA[BcCkDsE{ƨ_{S[c4|ԛ#BӀ T}ӈT{@A 4?T<ҧ{`T_{w"$~EcCfBӤR #@SA [B{Ũ_ҡDqq?T @z?T,q@z~$<{@Sc$@[`Ek@ $@7I T<^{`@xB@x@  @!T@.v տ>3TTUu&h58&@E &7@@b@"SA[BcCkD{Ǩ_ տ>+H T@T uyh58`@y@A?@@T@.v տ>/H TT uaBh58`&@a""@B_@@T@.pv Ձ@xC_ T Ss T`}uz&@AӁ@B  B@C @}zN#ѳ@&dj`C+@`a l+@`@ աcއ/@`al/@`@҇3@`"a*l3@`"@rUb"Au ?TB@C@} !@9aB9~A@9a9B@9bB9ZsҦ}Ӱ~~`@@Typ&@@y9a@?@TyB}@Cˠ~o7p?{{_ $*06 this->size() (which is %zu) [bt] (DMLC_LOG_STACK_TRACE_DEPTH%zu/home/runner/work/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/utils.hread can not have position excceed buffer lengthwrite position exceed fixed buffer size/home/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/proxy_dmatrix.hSlicing DMatrix is not supported for Proxy DMatrix./home/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/adapter.hCheck failed: at_first_Cannot reset IteratorAdapter/home/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../common/common.hXGBoost version not compiled with GPU support.Bit fieldBooleanIntegerUnsigned integerFloating pointComplex floating pointTimedeltaDatetimeObjectStringUnicodeOther/home/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/array_interface.hInvalid type code: in `typestr' of input array. Please verify the `__cuda_array_interface__' of your input data complies to: https://docs.scipy.org/doc/numpy/reference/arrays.interface.html Or open an issue./home/runner/work/ml-builds/ml-builds/xgboost/src/c_api/c_api.ccDMatrix/Booster has not been intialized or has already been disposed.binary saving only supported by SimpleDMatrixCheck failed: type >= 1 && type <= 4XGDMatrixSetGroup is deprecated, use `XGDMatrixSetUIntInfo` instead.groupCheck failed: p_outCheck failed: p_mCheck failed: mCurrent DMatrix type does not support set data.map::at ( vs. vector::_M_default_appendNot implemented.feature_namefeature_typeUnknown field for Booster feature info:wjson/home/runner/work/ml-builds/ml-builds/xgboost/src/c_api/c_api_utils.hCheck failed: chunksize == groupsUnknown prediction type:std::accumulate(shape.cbegin(), shape.cend(), 1, std::multiplies<>{}) == chunksize * rows/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/json.hInvalid cast, from learnergradient_boostergblineargbtree_train_paramnum_parallel_treestoiUnknown booster:str.size() > 2str[0] == '{'versionMissing `version' field for array interfacestreamOnly version <= 3 of `__cuda_array_interface__' are supported.typestrMissing `typestr' field for array interfacetypestr.size() == 3`typestr' should be of format .typestr.front() != '>'Big endian is not supported.shapeMissing `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)j_shape.size() == 2Only 1-D and 2-D arrays are supported.maskj_shape.size() == 1basic_string::at: __n (which is %zu) >= this->size() (which is %zu)type_length == 1mask 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.stridesstrides.size() == 1get(strides.at(0)) == type_lengthMemory should be contigious. is not supported.shape.first * shape.second == 0Empty data with non-zero shape.n_bits == num_rowsShape of bit mask doesn't match data shape. XGBoost doesn't support internal broadcasting.Check failed: array.find("mask") == array.cend()Masked array is not yet supported.j_strides.size() <= 2Check failed: validInvalid strides in array.get(jinterface).size() == 1Column: Check failed: num_rows == 1 || num_cols == 1Array should be a vector instead of matrix.DMatrix has not been intialized or has already been disposed.iteration_beginiteration_endtrainingstrict_shapemissingInvalid missing value: cache_idget(config["cache_id"]) == 0Cache ID is not supported yetCheck failed: p_predt/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/feature_map.hfid == static_cast(names_.size())qintfloatunknown feature type, use i for indicator and q for quantitytextXGBoost distributed mode detected, will split data among workersautonthreadstatic_cast*>(handle) ->get() ->Info() .group_ptr_.size() == 0Uslice does not support group structure__', Possible Arguments: ---------------- Cannot find argument 'Check failed: eCheck failed: ec == std::errc()%ldfalseUnknown global parameters: { }vector::_M_range_insertCheck failed: columns_ == data::kAdapterUnknownSize || columns_ == batch.columnsNumber of columns between batches changed from 00010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899@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!NaNInfinity0E0N7xgboost6common6ColumnIhEEN7xgboost6common6ColumnItEEN7xgboost6common6ColumnIjEEN7xgboost6common11DenseColumnIhEEN7xgboost6common12SparseColumnIhEEN7xgboost6common11DenseColumnItEEN7xgboost6common12SparseColumnItEEN7xgboost6common11DenseColumnIjEEN7xgboost6common12SparseColumnIjEE/home/runner/work/ml-builds/ml-builds/xgboost/src/common/hist_util.cc/home/runner/work/ml-builds/ml-builds/xgboost/src/common/hist_util.hibegin + inst.size() == iendsibling.size() == sizeparent.size() == sizevector::_M_fill_insert/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/data.hCheck failed: impl_ != nullptrcut.Values().size() > 0Ubatch_size < offset_vec.size()curent_bin_size == kUint32BinsTypeSizebins_type_size == kUint32BinsTypeSize/home/runner/work/ml-builds/ml-builds/xgboost/src/common/column_matrix.hsizeof(BinIdxType) == bins_type_size_Check failed: false/home/runner/work/ml-builds/ml-builds/xgboost/src/common/host_device_vector.ccSize() == other.Size()Size() == other.size()N7xgboost6common16PeekableInStreamEN7xgboost6common15FixedSizeStreamEbasic_string::substr/home/runner/work/ml-builds/ml-builds/xgboost/src/common/io.ccCheck failed: out://file://Opening failed: /home/runner/work/ml-builds/ml-builds/xgboost/src/common/io.hNot implementedpointer_ <= buffer_.size()$0size == 0Check failed: worker_feature.data()mingap=, maxgap=, wgap=Check failed: size <= sa.size + sb.sizebug in combinecount <= total_entriessketches_.size() == info.num_col_worker_segments.size() >= 1columns_size_.size() != 0Check failed: nlevel <= std::max(static_cast(1), static_cast(limit_size * eps))invalid init parameterbase_rowid < group_ptr.back()Row: is not found in any group.num_cuts.size() == 0n_columns == sketches_.size()Number of columns differs across workersCheck failed: reduced[i].dataCheck failed: a.dataCheck failed: a.data && reduced[fid].datacuts->cut_values_.HostVector().size() <= std::numeric_limits::max()cut_size > cuts->cut_ptrs_.HostVector().back()4 >St19_Sp_make_shared_tagSt23_Sp_counted_ptr_inplaceIN7xgboost16HostDeviceVectorIjEESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE/home/runner/work/ml-builds/ml-builds/xgboost/src/common/random.harray.size() == weights.size()/home/runner/work/ml-builds/ml-builds/xgboost/src/common/random.ccfeatures.size() > 0N4dmlc9parameter10FieldEntryIN7xgboost6common27ProbabilityDistributionTypeEEEvalue for Parameter exceed bound [ should be greater equal to should be smaller equal to Required parameter of is not presentedInvalid Parameter format for expect but value=' optional, default=, requiredInvalid Input: '', valid values are: /home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./parameter.henum_back_map_.count(value) != 0UValue not found in enum declaredoptional, default=/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././strtonum.h*p == ')'Invalid NAN literalNo conversion could be performedpos <= value.length()Some trailing characters could not be parsed: 'Out of range value for , value='Out of range valueEnum ( exisit!) Enums: ), aft_loss_distributionkey has already been registered in normallogisticextremeChoice of distribution for the noise term in Accelerated Failure Time modelaft_loss_distribution_scaleScaling factor used to scale the distribution in Accelerated Failure Time modelAFTParam/home/runner/work/ml-builds/ml-builds/xgboost/src/common/timer.ccTimer for did not get stopped properly.s, calls @ usstatisticcountelapsed======== Monitor: ========From rank: version:Incorrect version format found in binary file. Binary file from XGBoost < 1.0.0 is no longer supported. Please generate it again./home/runner/work/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: 71-' =  &&6<.$*2:BHgca_][YWMk3/+'#5Zf@~r@'# +$cS]KCk(z(2nH  v}c N7xgboost7DMatrixENSt6thread10_Impl_baseEN7xgboost4data11FileAdapterEN4dmlc12ScopedThreadEN4dmlc8DataIterIN7xgboost10SparsePageEEEN7xgboost4data24ExternalMemoryPrefetcherINS_10SparsePageEEEN4dmlc8DataIterIN7xgboost7CSCPageEEEN7xgboost4data24ExternalMemoryPrefetcherINS_7CSCPageEEEN4dmlc8DataIterIN7xgboost13SortedCSCPageEEEN7xgboost4data24ExternalMemoryPrefetcherINS_13SortedCSCPageEEEN4dmlc12ThreadedIterIN7xgboost7CSCPageEEEN4dmlc12ThreadedIterIN7xgboost13SortedCSCPageEEEN4dmlc8DataIterIN7xgboost11EllpackPageEEEN7xgboost4data24ExternalMemoryPrefetcherINS_11EllpackPageEEEN4dmlc12ThreadedIterIN7xgboost10SparsePageEEENSt6thread5_ImplISt12_Bind_simpleIFZN7xgboost4data16SparsePageWriterINS2_10SparsePageEEC4ERKSt6vectorINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEESaISD_EESH_mEUlvE_vEEEEN4dmlc12ThreadedIterIN7xgboost11EllpackPageEEESt15_Sp_counted_ptrIPN7xgboost10SparsePageELN9__gnu_cxx12_Lock_policyE2EEZN7xgboost4data24ExternalMemoryPrefetcherINS_10SparsePageEEC4ERKNS0_9CacheInfoEEUlPPS2_E_ZN7xgboost4data24ExternalMemoryPrefetcherINS_10SparsePageEEC4ERKNS0_9CacheInfoEEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterIN7xgboost10SparsePageEE4InitESt8functionIFbPPS5_EES7_IFvvEEEUlvE_vEEEESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN7xgboost4data16SparsePageWriterINS3_10SparsePageEEC4ERKSt6vectorINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEESaISE_EESI_mEUlvE_vEEEESaISM_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterIN7xgboost10SparsePageEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEESaISI_ELN9__gnu_cxx12_Lock_policyE2EE/home/runner/work/ml-builds/ml-builds/xgboost/src/data/data.ccCheck failed: v.DeviceIdx() == GenericParameter::kCpuId || device == GenericParameter::kCpuId || v.DeviceIdx() == deviceData is resided on a different device than `gpu_id`. Device that data is on: `gpu_id` for XGBoost: /home/runner/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.hCheck failed: mutex_.try_lock()Multiple threads attempting to use prefetcher/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/threadediter.hCheck failed: out_data_ != NULLCalling Value at beginning or end?float32float64bool8int32int8int16int64/home/runner/work/ml-builds/ml-builds/xgboost/src/data/../data/adapter.hUnknown data table type.Couldn't remove external memory cache file ; you may want to remove it manuallyCache file exists already; Is there another DMatrix with the same cache prefix? It can be caused by previously used DMatrix that hasn't been collected by language environment garbage collector. Otherwise please remove it manually.labelbase_marginlabel_lower_boundlabel_upper_boundfeature_weightsUnknown float field name: group_ptrUnknown uint32 field name: Unknown data type for getting meta info./home/runner/work/ml-builds/ml-builds/xgboost/src/data/../common/common.hself_offset.size() == other_offset.size()self_data.size(): other_data.size(): beg <= data.size()ptr < offset.size()this->base_margin_.Size() % this->num_row_ == 0Incorrect size of base margin vector./home/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_writer.hname_shards.size() == format_shards.size()Unknown format type num_rownum_colnum_nonzerolabelslabels_lower_boundlabels_upper_boundfeature_namesfeature_typesfield_cnt == kNumFieldWrong number of fieldscategoricalAll feature_types must be one of {int, float, i, q, categorical}.size == this->num_col_Length of must be equal to number of columns.Unknown feature info name: Unknown feature info: group_ptr_.size() == weights_.Size() + 1Size of weights must equal to number of groups when ranking group is used.group_ptr_.back() == num_row_Invalid group structure. Number of rows obtained from groups doesn't equal to actual number of rows given by data.weights_.Size() == num_row_Size of weights must equal to number of rows.labels_.Size() == num_row_Size of labels must equal to number of rows.labels_lower_bound_.Size() == num_row_Size of label_lower_bound must equal to number of rows.feature_weigths.Size() == num_col_Size of feature_weights must equal to number of columns.labels_upper_bound_.Size() == num_row_Size of label_upper_bound must equal to number of rows.num_nonzero_ <= num_col_ * num_row_base_margin_.Size() % num_row_ == 0Size of base margin must be a multiple of number of rows.cache_shards.size() != 0U.fmt-rawkey >= builder_base_row_offsetthis->num_col_ == that.num_col_Number of columns must be consistent across batches.that.group_ptr_.size() != 0nthread == 1Input data contains `inf` or `nan`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)MetaInfo: Invalid format. Check failed: strm->Read(&name)name == expected_name Expected field: , got: Check failed: strm->Read(&type_val)Check failed: type == expected_typeExpected field of type: got field type: Check failed: strm->Read(&is_scalar)Check failed: is_scalarExpected field to be a scalar; got a vectorCheck failed: strm->Read(field)Check failed: !is_scalar to be a vector; got a scalarCheck failed: strm->Read(&shape.first)Check failed: strm->Read(&shape.second)shape.second == 1Number of columns is expected to be 1.major == 1Binary DMatrix generated by XGBoost: is no longer supported. Please process and save your data in current version: again.Check failed: fi->Read(&num_field)MetaInfo: invalid formatnum_field >= expectedMetaInfo: insufficient number of fields (expected at least fields, but the binary file only contains fields.)MetaInfo: the given binary file contains extra fields which will be ignored.Unknown data typeWeights must be positive values.qidCheck failed: non_dec`qid` must be sorted in non-decreasing order along with data.Feature weight must be greater than 0.Unknown key for MetaInfo: info.name_shards.size() != 0UCheck failed: finfo->Read(&tmagic)tmagic == kMagicinvalid format, magic number mismatchCheck failed: fi->Read(&format)Invalid page formatNo threadCheck failed: !producer_sig_processed_.load(std::memory_order_acquire)Check 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) != kDestroySparsePageWriter Finished writing to .row.pagepage->Size() == 0SparsePageSource Finished writing to Check failed: qids.empty() || qids.size() == info.num_row_cache_file.find('#') == std::string::nposOnly one `#` is allowed in file path for cache file specification..r-XGBOOST_TEST_NPARTLoad part of data parts matrix with entries loaded from .group groups are loaded from .base_margin base_margin are loaded from .weight weights are loaded from csvlibsvmNo format parameter is provided in input uri, but found file extension: . Consider providing a uri parameter: filename?format=No format parameter is provided in input uri. Choosing default parser in dmlc-core. Consider providing a uri parameter like: filename?format=csvEncountered parser error: /home/runner/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page.ccInternal Error: XGBoost is not compiled with CUDA but EllpackPage is required.ellpack.page/home/runner/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page_source.ccInternal Error: XGBoost is not compiled with CUDA but EllpackPageSource is requiredN7xgboost4data13SimpleDMatrixEN7xgboost17BatchIteratorImplINS_10SparsePageEEEN7xgboost4data23SimpleBatchIteratorImplINS_10SparsePageEEEN7xgboost17BatchIteratorImplINS_7CSCPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_7CSCPageEEEN7xgboost17BatchIteratorImplINS_13SortedCSCPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_13SortedCSCPageEEEN7xgboost17BatchIteratorImplINS_11EllpackPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_11EllpackPageEEE/home/runner/work/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.hCheck failed: page_ != nullptr/home/runner/work/ml-builds/ml-builds/xgboost/src/data/adapter.h/home/runner/work/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.ccCheck failed: in_stream->Read(&tmagic)invalid input file formatCheck failed: param != BatchParam{}Batch parameter is not initialized.param.gpu_id >= 0param.max_bin >= 2Check failed: (std::is_same::value)Expecting CSCAdapterN7xgboost4data23SparseBatchIteratorImplINS0_24ExternalMemoryPrefetcherINS_10SparsePageEEES3_EEN7xgboost4data23SparseBatchIteratorImplINS0_24ExternalMemoryPrefetcherINS_7CSCPageEEES3_EEN7xgboost4data23SparseBatchIteratorImplINS0_24ExternalMemoryPrefetcherINS_13SortedCSCPageEEES3_EEN7xgboost4data23SparseBatchIteratorImplINS0_24ExternalMemoryPrefetcherINS_11EllpackPageEEES3_EEN7xgboost4data17SparsePageDMatrixEZN7xgboost4data24ExternalMemoryPrefetcherINS_7CSCPageEEC4ERKNS0_9CacheInfoEEUlPPS2_E_ZN7xgboost4data24ExternalMemoryPrefetcherINS_7CSCPageEEC4ERKNS0_9CacheInfoEEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterIN7xgboost7CSCPageEE4InitESt8functionIFbPPS5_EES7_IFvvEEEUlvE_vEEEEZN7xgboost4data24ExternalMemoryPrefetcherINS_13SortedCSCPageEEC4ERKNS0_9CacheInfoEEUlPPS2_E_ZN7xgboost4data24ExternalMemoryPrefetcherINS_13SortedCSCPageEEC4ERKNS0_9CacheInfoEEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterIN7xgboost13SortedCSCPageEE4InitESt8functionIFbPPS5_EES7_IFvvEEEUlvE_vEEEESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterIN7xgboost7CSCPageEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEESaISI_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterIN7xgboost13SortedCSCPageEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEESaISI_ELN9__gnu_cxx12_Lock_policyE2EE/home/runner/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_dmatrix.hSlicing DMatrix is not supported for external memory.Check failed: source_ != nullptr/home/runner/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_writer.hCheck failed: *out_page == nullptrCheck failed: qrecycle_.Pop(out_page).col.pageWriting to MB/s, writtenCSCPageSource: Finished writing to .sorted.col.pageSortedCSCPageSource: Finished writing to /home/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.ccN7xgboost4data16SparsePageFormatINS_10SparsePageEEEN7xgboost4data19SparsePageRawFormatINS_10SparsePageEEEN7xgboost4data16SparsePageFormatINS_7CSCPageEEEN7xgboost4data19SparsePageRawFormatINS_7CSCPageEEEN7xgboost4data16SparsePageFormatINS_13SortedCSCPageEEEN7xgboost4data19SparsePageRawFormatINS_13SortedCSCPageEEE*N7xgboost4dataUlvE_E*N7xgboost4dataUlvE0_E*N7xgboost4dataUlvE1_E/home/runner/work/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 filefi->Read(dmlc::BeginPtr(data_vec), (page->data).Size() * sizeof(Entry)) == (page->data).Size() * sizeof(Entry)fid + 1 < disk_offset_.size()disk_offset_[fid] > curr_offsetfi->Read(dmlc::BeginPtr(data_vec) + offset_vec[i], size_to_read * sizeof(Entry)) == size_to_read * sizeof(Entry)St23_Sp_counted_ptr_inplaceIN7xgboost10SparsePageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EE/home/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.ccoffset + n_rows + 1 <= in_offset.size()h_offset.size() > 0n_entries == in_offset.at(offset + n_rows) - in_offset.at(offset)out->Size() != 0N4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEES8_EEN4dmlc9parameter10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEEN7xgboost5ModelEN7xgboost12ConfigurableEN7xgboost15GradientBoosterEN7xgboost3gbm8GBLinearE*N7xgboost3gbmUlPKNS_17LearnerModelParamEE_Egpu_coord_descent/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear.ccgblinear does not support prediction of leaf index/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/gbm.hInplace predict is not supported by current booster.Slice is not supported by current booster.modelPredictBatchInternalbase_margin.size() == nsize * ngroup/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.hfi->Read(¶m_, sizeof(param_)) == sizeof(param_)DoBoostlayer_begin == 0Linear booster does not support prediction range.layer_end == 0PredictBatch/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.h { "bias": [ ], "weight": [ ] }bias: weight: get(in["name"]) == "gblinear"updaterstringshotgunUpdate algorithm for linear model. One of shotgun/coord_descenttoleranceStop if largest weight update is smaller than this number.max_row_perbatchlong (non-negative)Maximum rows per batch.GBLinearTrainParamGBLinear/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/../common/common.hgblinear_train_paramCheck failed: this->updater_Linear booster, implement generalized linear model.N7xgboost3gbm13GBLinearModelEDeprecatedGBLinearModelParam/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbm.ccUnknown gbm type 4, *N7xgboost3gbmUlPKNS_17LearnerModelParamEE_E*N7xgboost3gbmUlPKNS_17LearnerModelParamEE0_EN4dmlc9parameter10FieldEntryIN7xgboost10TreeMethodEEEN4dmlc9parameter10FieldEntryIN7xgboost15TreeProcessTypeEEEN4dmlc9parameter10FieldEntryIN7xgboost13PredictorTypeEEEN7xgboost3gbm6GBTreeEN7xgboost3gbm4DartE/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.ccTree method is automatically selected to be 'approx' for distributed training.Tree method is automatically set to 'approx' since external-memory data matrix is used.Tree method is automatically selected to be 'approx' for faster speed. To use old behavior (exact greedy algorithm on single machine), set tree_method to 'exact'.Using tree method: grow_histmaker,prunegrow_colmaker,pruneTree method is selected to be 'hist', which uses a single updater grow_quantile_histmaker.grow_quantile_histmakergrow_gpu_histUnknown tree_method () detectedCheck failed: configured_XGBoost version not compiled with OneAPI support.Check failed: cpu_predictor_Data is on CUDA device, but XGBoost is not compiled with CUDA support.weight_drop/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.htree_begin <= tree_endCheck failed: predictori >= p_out_preds->versionp_out_preds->predictions.Size() == predts.predictions.Size()Unsupported data type for inplace predict.Check failed: successpredts.predictions.Size() == out_preds->predictions.Size()tparam_.num_parallel_tree != 0model_.learner_model_param->num_output_group != 0out_preds->version == 0tree_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.CommitModelups.size() == updaters_.size()Internal Error: mismatched updater sequence. Specified updaters: Actual updaters: get(in["name"]) == "gbtree"get(in["name"]) == "dart"Check failed: p_gbtreelayer_end > layer_beginstep >= 1Check failed: this->model_.trees_to_update.empty()in_it < tree_endCheck failed: p_dartCheck failed: p_dart->weight_drop_.empty()drop trees, weight = GBTreeModelParamnum_treesNumber of features used for training and prediction.size_leaf_vectorReserved option for vector tree. has not been registered in Alias Number of parallel trees constructed during each iteration. This option is used to support boosted random forest.updater_seqTree updater sequence.process_typedefaultupdateWhether to run the normal boosting process that creates new trees, or to update the trees in an existing model.predictorcpu_predictorgpu_predictoroneapi_predictorPredictor algorithm typetree_methodapproxexacthistgpu_histChoice of tree construction method.GBTreeTrainParamsample_typeuniformweightedDifferent types of sampling algorithm.normalize_typeforestDifferent types of normalization algorithm.rate_dropFraction of trees to drop during the dropout.one_dropbooleanWhether at least one tree should always be dropped during the dropout.skip_dropProbability of skipping the dropout during a boosting iteration.learning_rateLearning rate(step size) of update.etaDartTrainParamCheck failed: !updaters_.front()->CanModifyTree()Updater: `` can not be used to create new trees. Set `process_type` to `update` if you want to update existing trees.Check failed: up->CanModifyTree()can not be used to modify existing trees. Set `process_type` to `default` if you want to build new trees.model_.trees.size() < model_.trees_to_update.size()No more tree left for updating. For updating existing trees, boosting rounds can not exceed previous training roundsgpair->Size() == p_fmat->Info().num_row_Mismatching size between number of rows from input data and size of gradient vector.GBTreeDANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.Check failed: this->configured_Check failed: tparam_.GetInitialised()Using updaters: BoostNewTreesngroup != 0in_gpair->Size() % ngroup == 0Umust have exactly ngroup * nrow gpairsspecified_updaterdart_train_paramLoading from a raw memory buffer on CPU only machine. Changing predictor to auto.Loading from a raw memory buffer on CPU only machine. Changing tree_method to hist.vector::reserveTree booster, gradient boosted trees.Tree booster, dart.N7xgboost3gbm11GBTreeModelE/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.ccparam.num_trees == static_cast(trees.size())fi->Read(¶m, sizeof(param)) == sizeof(param)GBTree: invalid model filefi->Read(dmlc::BeginPtr(tree_info), sizeof(int32_t) * param.num_trees) == sizeof(int32_t) * param.num_treesgbtree_model_paramtreesidtree_infoparam.num_trees == static_cast(trees.size())GlobalConfigurationverbosityFlag to print out detailed breakdown of runtime.use_rmmWhether to use RAPIDS Memory Manager to allocate GPU memory in XGBoostN4dmlc12SerializableEN7xgboost7LearnerEN4dmlc9parameter10FieldEntryIN7xgboost13DataSplitModeEEEN7xgboost20LearnerConfigurationEN7xgboost9LearnerIOEN7xgboost11LearnerImplE/home/runner/work/ml-builds/ml-builds/xgboost/src/learner.ccStarting in XGBoost , the default evaluation metric used with the objective '' was changed from '' to ''. Explicitly set eval_metric if you'd like to restore the old behavior.Check failed: !this->need_configuration_Check failed: tparam_.dsplit != DataSplitMode::kAutoPrecondition violated; dsplit cannot be 'auto' in distributed modeColumn-wise data split is currently not supported.ModelConfigbase_scorenum_featurenum_classCall Configure before saving model.learner_model_paramobjectiveattributeslearner_model_param_.num_feature == p_fmat->Info().num_col_Number of columns does not match number of features in booster.Empty dataset at worker: learner_model_param_.num_feature >= p_fmat->Info().num_col_EvalOneItererrorlogloss1.3.0binary:logitrawauc1.4.0multi:softmaxmulti:softprobmloglossCheck failed: gbm_ != nullptrPredict must happen after Load or configurationbinary:logisticmerrorUpdateOneIterPredictRawPredictionsGetGradientGradientsmultiple_predictions <= 1Perform one kind of prediction at a time.Global 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.LearnerModelParamLegacyseedlongRandom number seed during training.random_stateseed_per_iterationSeed PRNG determnisticly via iterator number, this option will be switched on automatically on distributed mode.Number of threads to use.n_jobsThe primary GPU device ordinal.fail_on_invalid_gpu_idFail with error when gpu_id is invalid.gpu_page_sizeGPU page size when running in external memory mode.validate_parametersEnable checking whether parameters are used or not.n_gpus Deprecated. Single process multi-GPU training is no longer supported. Please switch to distributed training with one process per GPU. This can be done using Dask or Spark. See documentation for details.GenericParameter/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/generic_parameters.h n_gpus: dsplitcolrowData split mode for distributed training.disable_default_eval_metricFlag to disable default metric. Set to >0 to disableboosterGradient booster used for training.reg:squarederrorObjective function used for obtaining gradient.LearnerTrainParamCheck failed: matrix.firstCheck failed: !matrix.second.ref.expired()num_col <= static_cast(std::numeric_limits::max())Unfortunately, XGBoost does not support data matrices with features or greatermparam_.num_feature != 00 feature is supplied. Are you using raw Booster interface?num_output_groupmax_delta_stepcount:poisson0.7learner_train_parammetricsgeneric_paramBoostOneIterCheck failed: IsA(in)Learnernum_roundCONFIG-offset:Unsupported prediction type:Invalid parameter "" contains whitespace. Parameters: { ", } might not be used. This may not be accurate due to some parameters are only used in language bindings but passed down to XGBoost core. Or some parameters are not used but slip through this verification. Please open an issue if you find above cases. Configure;binfbegin_layer >= 0fp.Read(&header[0], header.size()) == serialisation_header_.size()Check failed: header == serialisation_header_ If you are loading a serialized model (like pickle in Python) generated by older XGBoost, please export the model by calling `Booster.save_model` from that version first, then load it back in current version. There's a simple script for helping the process. See: https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html for reference to the script, and more details about differences between saving model and serializing. fp.Read(&sz, sizeof(sz)) == sizeof(sz)sz > 0bs64header != "bs64"Base64 format is no longer supported in brick.fp.Read(&header[0], 4) == 4Ufi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_)BoostLearner: wrong model formatCheck failed: fi->Read(&tparam_.objective)Check failed: fi->Read(&tparam_.booster)SAVED_PARAM_count_poisson_max_delta_stepmulti:Loading model from XGBoost < 1.0.0, consider saving it again for improved compatibility/home/runner/work/ml-builds/ml-builds/xgboost/src/linear/linear_updater.ccUnknown linear updater Learning rate of each update.reg_lambdaL2 regularization on weights.reg_alphaL1 regularization on weights.feature_selectorcyclicshufflethriftygreedyrandomFeature selection or ordering method.lambdaalphaLinearTrainParamN7xgboost13LinearUpdaterEN7xgboost6linear15FeatureSelectorEN7xgboost6linear21CyclicFeatureSelectorEN7xgboost6linear22ShuffleFeatureSelectorEN7xgboost6linear21RandomFeatureSelectorEN7xgboost6linear21GreedyFeatureSelectorEN7xgboost6linear22ThriftyFeatureSelectorEN7xgboost6linear17CoordinateUpdaterE*N7xgboost6linearUlvE_EUpdateFeatureCoordinateParamtop_kThe number of top features to select in 'thrifty' feature_selector. The value of zero means using all the features./home/runner/work/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.hunknown coordinate selector: CoordinateUpdaterlinear_train_paramcoordinate_paramcoord_descentUpdate linear model according to coordinate descent algorithm. (2 N7xgboost6linear14ShotgunUpdaterE*N7xgboost6linearUlvE_E/home/runner/work/ml-builds/ml-builds/xgboost/src/linear/updater_shotgun.ccUnsupported feature selector for shotgun updater. Supported options are: {cyclic, shuffle}Update linear model according to shotgun coordinate descent algorithm.!'WARNING: DEBUG: INFO: 4 >N7xgboost6MetricEN7xgboost6metric7EvalAUCE*N7xgboost6metricUlPKcE_E/home/runner/work/ml-builds/ml-builds/xgboost/src/metric/../common/common.h/home/runner/work/ml-builds/ml-builds/xgboost/src/metric/auc.ccinfo.group_ptr_.size() >= 2/home/runner/work/ml-builds/ml-builds/xgboost/src/metric/auc.hInvalid group with less than 3 samples is found on worker . Calculating AUC value requires at least 2 pairs of samples.n_classes != 0Check failed: !labels.empty()labels.size() == predts.size()info.weights_.Size() == info.group_ptr_.size() - 1info.group_ptr_.back() == info.labels_.Size()auc <= 1Total AUC across groups: , valid groups: Dataset contains only positive or negative samples.auc <= 1.0fReceiver Operating Characteristic Area Under the Curve.N7xgboost6metric13EvalEWiseBaseINS0_11EvalRowRMSEEEEN7xgboost6metric13EvalEWiseBaseINS0_12EvalRowRMSLEEEEN7xgboost6metric13EvalEWiseBaseINS0_10EvalRowMAEEEEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowMAPEEEEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowMPHEEEEN7xgboost6metric13EvalEWiseBaseINS0_14EvalRowLogLossEEEN7xgboost6metric13EvalEWiseBaseINS0_20EvalPoissonNegLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_17EvalGammaDevianceEEEN7xgboost6metric13EvalEWiseBaseINS0_16EvalGammaNLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_9EvalErrorEEEN7xgboost6metric13EvalEWiseBaseINS0_18EvalTweedieNLogLikEEE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E*N7xgboost6metricUlPKcE1_E*N7xgboost6metricUlPKcE2_E*N7xgboost6metricUlPKcE3_E*N7xgboost6metricUlPKcE4_E*N7xgboost6metricUlPKcE5_E*N7xgboost6metricUlPKcE6_E*N7xgboost6metricUlPKcE7_E*N7xgboost6metricUlPKcE8_E*N7xgboost6metricUlPKcE9_Egamma-nloglikgamma-deviancepoisson-nloglikmphemapemaermslermsetweedie-nloglik@/home/runner/work/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)%fsscanf(param, "%f", &threshold_) == 1unable to parse the threshold value for the error metricpreds.Size() == info.labels_.Size()label and prediction size not match, hint: use merror or mlogloss for multi-class classificationRooted mean square error.Rooted mean square log error.Mean absolute error.Mean absolute percentage error.Mean Pseudo Huber error.Negative loglikelihood for logistic regression.Negative loglikelihood for poisson regression.Residual deviance for gamma regression.Negative log-likelihood for gamma regression.Binary classification error.tweedie-nlogliktweedie-nloglik@rho for tweedie regression./home/runner/work/ml-builds/ml-builds/xgboost/src/metric/metric.ccUnknown metric function Cannot find a GPU metric builder for metric . Resorting to the CPU builderN7xgboost6metric14EvalMClassBaseINS0_14EvalMatchErrorEEEN7xgboost6metric14EvalMatchErrorEN7xgboost6metric14EvalMClassBaseINS0_16EvalMultiLogLossEEEN7xgboost6metric16EvalMultiLogLossE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E/home/runner/work/ml-builds/ml-builds/xgboost/src/metric/multiclass_metric.cupreds.Size() == 0Check failed: preds.Size() % info.labels_.Size() == 0label and prediction size not matchnclass >= 1Umlogloss 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), num_class= but found in labelMulticlass classification error.Multiclass negative loglikelihood., 62N7xgboost6metric14EvalRankConfigEN7xgboost6metric7EvalAMSEN7xgboost6metric8EvalRankEN7xgboost6metric13EvalPrecisionEN7xgboost6metric8EvalNDCGEN7xgboost6metric7EvalMAPEN7xgboost6metric7EvalCoxEN7xgboost6metric9EvalAucPRE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E*N7xgboost6metricUlPKcE1_E*N7xgboost6metricUlPKcE2_E*N7xgboost6metricUlPKcE3_E*N7xgboost6metricUlPKcE4_Ecox-nloglikaucpr%u[-]?prendcgmap/home/runner/work/ml-builds/ml-builds/xgboost/src/metric/rank_metric.ccAMS must be in format ams@kams@label size predict size not matchgptr.size() != 0Umust specify group when constructing rank filegptr.back() == preds.Size()EvalRank: group structure must match number of predictioninfo.labels_.Size() != 0Ulabel set cannot be emptygptr.back() == info.labels_.Size()EvalAucPR: group structure must match number of predictiondat[1] > 0.0fAUC-PR: the dataset only contains pos or neg samplesdat[0] <= dat[1]AUC-PR: AUC > 1.0amsAMS metric for higgs.Area under PR curve for both classification and rank.precision@k for rank.ndcg@k for rank.map@k for rank.Negative log partial likelihood of Cox proportioanl hazards model.Check failed: !distributedCox metric does not support distributed evaluationmetric AMS do not support distributed evaluationbest-ams-ratio=Check failed: !auc_errorAUC-PR: error in calculationN7xgboost6metric20AFTNLogLikDispatcherEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common18NormalDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common20LogisticDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common19ExtremeDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_30EvalIntervalRegressionAccuracyEEE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_Eaft-nloglikinterval-regression-accuracy/home/runner/work/ml-builds/ml-builds/xgboost/src/metric/survival_metric.cuCheck failed: metric_AFT metric must be configured first, with distribution type and scalepreds.Size() == info.labels_lower_bound_.Size()preds.Size() == info.labels_upper_bound_.Size()ndata == labels_upper_bound.Size()Unknown probability distributionaft_loss_paramNegative log likelihood of Accelerated Failure Time model.N7xgboost11ObjFunctionEN7xgboost3obj6AFTObjE*N7xgboost3objUlvE_E/home/runner/work/ml-builds/ml-builds/xgboost/src/objective/../common/transform.hNot part of device code. WITH_CUDA: /home/runner/work/ml-builds/ml-builds/xgboost/src/objective/aft_obj.cuinfo.labels_lower_bound_.Size() == ndatainfo.labels_upper_bound_.Size() == ndatainfo.weights_.Size() == ndataNumber of weights should be equal to number of data points.Unrecognized distributionsurvival:aftAFT loss functionN7xgboost3obj8HingeObjE*N7xgboost3objUlvE_Ebinary:hinge/home/runner/work/ml-builds/ml-builds/xgboost/src/objective/hinge.culabels are not correctly providedpreds.size=, label.size=Hinge loss. Expects labels to be in [0,1f]N7xgboost3obj20SoftmaxMultiClassObjE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_E/home/runner/work/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. label.Size() * num_class: num_class: preds.Size(): SoftmaxMultiClassObj: label must be in [0, num_class).SoftmaxMultiClassParamNumber of output class in the multi-class classification.softmax_multiclass_paramSoftmax for multi-class classification, output class index.Softmax for multi-class classification, output probability distribution.Objective candidate: /home/runner/work/ml-builds/ml-builds/xgboost/src/objective/objective.ccUnknown objective function: `` N7xgboost3obj13LambdaRankObjINS0_28PairwiseLambdaWeightComputerEEEN7xgboost3obj13LambdaRankObjINS0_24NDCGLambdaWeightComputerEEEN7xgboost3obj13LambdaRankObjINS0_23MAPLambdaWeightComputerEEE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_E*N7xgboost3objUlvE1_Enum_pairsampleNumber of pair generated for each instance.fix_list_weightNormalize the weight of each list by this value, if equals 0, no effect will happenLambdaRankParamrank:pairwisePairwise rank objective.rank:ndcgLambdaRank with NDCG as objective.rank:mapLambdaRank with MAP as objective./home/runner/work/ml-builds/ml-builds/xgboost/src/objective/rank_obj.cuComputing gradients on CPU.Check failed: gptr.size() != 0 && gptr.back() == info.labels_.Size()group structure not consistent with #rowsgroup ponter size: labels size: group pointer back: lambda_rank_paramN7xgboost3obj10RegLossObjINS0_16LinearSquareLossEEEN7xgboost3obj10RegLossObjINS0_15SquaredLogErrorEEEN7xgboost3obj10RegLossObjINS0_18LogisticRegressionEEEN7xgboost3obj10RegLossObjINS0_16PseudoHuberErrorEEEN7xgboost3obj10RegLossObjINS0_22LogisticClassificationEEEN7xgboost3obj10RegLossObjINS0_11LogisticRawEEEN7xgboost3obj17PoissonRegressionEN7xgboost3obj13CoxRegressionEN7xgboost3obj15GammaRegressionEN7xgboost3obj17TweedieRegressionE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_E*N7xgboost3objUlvE1_E*N7xgboost3objUlvE2_E*N7xgboost3objUlvE3_E*N7xgboost3objUlvE4_E*N7xgboost3objUlvE5_E*N7xgboost3objUlvE6_E*N7xgboost3objUlvE7_E*N7xgboost3objUlvE8_E*N7xgboost3objUlvE9_E/home/runner/work/ml-builds/ml-builds/xgboost/src/objective/regression_obj.cureg:linear is now deprecated in favor of reg:squarederror.survival:coxreg:gamma/home/runner/work/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: PoissonRegression: label must be nonnegativeGammaRegression: label must be positive.TweedieRegression: label must be nonnegativeLoss: label must be in [0,1] for logistic regressionreg:pseudohubererrorreg:logisticreg:squaredlogerrorlabel must be greater than -1 for rmsle so that log(label + 1) can be valid.RegLossParamscale_pos_weightScale the weight of positive examples by this factorPoissonRegressionParamMaximum delta step we allow each weight estimation to be. This parameter is required for possion regression.TweedieRegressionParamtweedie_variance_powerTweedie 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.Regression Pseudo Huber error.Logistic regression for binary classification task.Logistic regression for classification, output score before logistic transformation.reg:linearPossion regression for count data.Cox regression for censored survival data (negative labels are considered censored).Gamma regression for severity data.reg:tweedieTweedie regression for insurance data.tweedie_regression_parampoisson_regression_paramCheck failed: last_abs_y <= abs_yCoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed!reg_loss_paramzq`Wh  $PF?7bj/ZN7xgboost9predictor12CPUPredictorESt10shared_ptrIN7xgboost4data12DenseAdapterEESt10shared_ptrIN7xgboost4data10CSRAdapterEE*N7xgboost9predictorUlPKNS_16GenericParameterEE_E/home/runner/work/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.ccmodel.param.size_leaf_vector == 0size_leaf_vector is enforced to 0 so farmodel.learner_model_param->num_output_group != 0out_preds->Size() == nIgnoring the base margin, since it has incorrect length. The base margin must be an array of length [num_class] * [number of data points], i.e. * = Instead, all data points will use [number of data points], i.e. base_score = /home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/any.hCheck failed: type_ != nullptrThe any container is empty requested=Check failed: *(type_->ptype_info) == typeid(T)The stored type mismatch stored=m->NumColumns() == model.learner_model_param->num_featureNumber of columns in data must equal to trained model.ncolumns != 0out_preds->size() == p_fmat->Info().num_row_ * model.learner_model_param->num_output_groupMake predictions using CPU.N7xgboost9PredictorE/home/runner/work/ml-builds/ml-builds/xgboost/src/predictor/predictor.ccUnknown predictor type Check failed: container_.find(m) != container_.cend()_Map_base::atCheck failed: container_.at(m).ref.lock()[Internal error]: DMatrix: has expired./home/runner/work/ml-builds/ml-builds/xgboost/src/tree/constraints.ccnewsize != 0Failed to parse feature interaction constraint: With error: /home/runner/work/ml-builds/ml-builds/xgboost/src/tree/param.ccstd::floor(d) == dFound floating point number in interaction constraintsUnknown value type for interaction constraint:$N7xgboost7RegTreeEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryISt6vectorIiSaIiEEEES5_EEN4dmlc9parameter10FieldEntryISt6vectorIiSaIiEEEEN7xgboost13TreeGeneratorEN7xgboost13TextGeneratorEN7xgboost13JsonGeneratorEN7xgboost17GraphvizGeneratorE*N7xgboostUlRKNS_10FeatureMapERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE_E*N7xgboostUlRKNS_10FeatureMapERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE0_E*N7xgboostUlRKNS_10FeatureMapENSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE1_E/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/tree_model.cc Line , around ^``basic_string::replaceUnknown Model Builder:param.num_nodes == static_cast(nodes_.size())param.num_nodes == static_cast(stats_.size())param.deprecated_num_roots == 1param.num_nodes != 0/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././json.hch == '\"'Error at, Expect '"' but get 'unknown string escape \, Expect '"' but reach end of line ch == ',', JSON object expect '}' or ',' 'ch == ':', Expect ':' but get 'ch == '{', Expect '{' but get 'this->node_mean_values_.size() > 0Uidx < names_.size()FeatureMap feature index exceed boundUnknown feature map type.pos != std::string::nposthis->split_types_.size() == param.num_nodesthis->GetSplitCategoriesPtr().size() == param.num_nodescategories_segmentscategories_sizescategories_nodescategoriesj_end - j_begin != 0std::numeric_limits::min() != max_catunique_path[i].pweight == 0Unique path must have zero weightfi->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_deleted/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/tree_model.hparam.num_nodes < std::numeric_limits::max()number of nodes in the tree exceed 2^31Check failed: node.IsLeaf()num_nodesNumber of features used in tree construction.Size of leaf vector, reserved for vector treeTreeParamdoubleyes_color#0000FFEdge color when meets the node condition.no_color#FF0000Edge color when doesn't meet the node condition.rankdirTBPassed to graphiz via graph_attr.condition_node_paramsConditional node configurationleaf_node_paramsLeaf node configurationgraph_attrsAny other extra attributes for graphviz `graph_attr`.GraphvizParammin_split_lossMinimum loss reduction required to make a further partition.max_depthMaximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policymax_leavesMaximum number of leaves; 0 indicates no limit.max_binif using histogram-based algorithm, maximum number of bins per featuregrow_policydepthwiselossguideTree growing policy. 0: favor splitting at nodes closest to the node, i.e. grow depth-wise. 1: favor splitting at nodes with highest loss change. (cf. LightGBM)min_child_weightMinimum sum of instance weight(hessian) needed in a child.L2 regularization on leaf weightL1 regularization on leaf weightdefault_directionlearnrightDefault direction choice when encountering a missing valueMaximum delta step we allow each tree's weight estimate to be. If the value is set to 0, it means there is no constraintsubsampleRow subsample ratio of training instance.sampling_methodgradient_basedSampling method. 0: select random training instances uniformly. 1: select random training instances with higher probability when the gradient and hessian are larger. (cf. CatBoost)colsample_bynodeSubsample ratio of columns, resample on each node (split).colsample_bylevelSubsample ratio of columns, resample on each level.colsample_bytreeSubsample ratio of columns, resample on each tree construction.sketch_epsEXP Param: Sketch accuracy of approximate algorithm.sketch_ratioEXP Param: Sketch accuracy related parameter of approximate algorithm.cache_optEXP Param: Cache aware optimization.refresh_leafWhether the refresh updater needs to update leaf values.monotone_constraintsConstraint of variable monotonicityinteraction_constraintsConstraints 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 informationsplit_evaluatorelastic_net,monotonicThe criteria to use for ranking splitssparse_thresholdpercentage threshold for treating a feature as sparseenable_feature_groupingif >0, enable feature grouping to ameliorate work imbalance among worker threadsmax_conflict_ratewhen grouping features, how many "conflicts" to allow.conflict is when an instance has nonzero values for two or more features.default is 0, meaning features should be strictly complementary.max_search_groupwhen grouping features, how much effort to expend to prevent singleton groups. We'll try to insert each feature into existing groups before creating a new group for that feature; to save time, only up to (max_search_group) of existing groups will be considered. If set to zero, ALL existing groups will be examined.gammatree_paramn_nodes != 0loss_changesloss_changes.size() == n_nodessum_hessiansum_hessian.size() == n_nodesbase_weightsbase_weights.size() == n_nodesleft_childrenlefts.size() == n_nodesright_childrenrights.size() == n_nodesparentsparents.size() == n_nodessplit_indicesindices.size() == n_nodessplit_conditionsconds.size() == n_nodesdefault_leftdefault_left.size() == n_nodessplit_typen_nodes == split_categories_segments_.size()static_cast(deleted_nodes_.size()) == param.num_deletedthis->split_categories_segments_.size() == param.num_nodesget(out["tree_param"]["num_nodes"]) == std::to_string(param.num_nodes){nodes} {nodes}{{properties} {stat}, "children": [{left}, {right} {indent}]}{properties}{stat}{left}{indent} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "yes": {yes}, "no": {no}{nid}%u{depth}{fname}{yes}{no}{cond}{missing} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {left}, "no": {right}, "missing": {missing}{tabs}{tabs}{nid}:[{fname}<{cond}] yes={left},no={right},missing={missing}{tabs}{nid}:[f{fname}<{cond}] yes={left},no={right},missing={missing}{tabs}{nid}:leaf={leaf}{stats},cover={cover}{leaf}{cover}{stats}{parent}{stat} {left} {right}{parent}{ "nodeid": {nid}, "leaf": {leaf} {stat}}, "cover": {sum_hess} {sum_hess}{newline}{indent}{nodes}{newline} {nid} [ label="leaf={leaf-value}" {params}] {leaf-value}{params}{parent} {left} {right}digraph { graph [ rankdir={rankdir} ] {graph_attrs} {nodes}}{rankdir}{graph_attrs}, "gain": {loss_chg}, "cover": {sum_hess}{loss_chg},gain={loss_chg},cover={sum_hess}yesno, missing{child}{color}{branch}< {nid} [ label="{fname}{<}{cond}" {params}] {<} {nid} -> {child} [label="{branch}" color="{color}"] {nid}:[{fname}] yes={yes},no={no}Dump text representation of treeDump json representation of treedotDump graphviz representation of tree" edge graph [ {key}="{value}" ] {key}{value}The following parameters for graphviz are not recognized: Failed to parse graphviz parameters: /home/runner/work/ml-builds/ml-builds/xgboost/src/tree/tree_updater.ccUnknown tree updater N7xgboost11TreeUpdaterEN7xgboost4tree8ColMaker7BuilderEN7xgboost4tree8ColMakerE*N7xgboost4treeUlvE_Egrow_colmaker/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_colmaker.ccCheck failed: param_.cache_optSupport for `cache_opt' is removed in 1.0.0/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/param.hMax leaves and max depth cannot both be unconstrained.this->max_depth <= 31max_depth can not be greater than 31 as that might generate 2 ** 32 - 1 nodes.ridx < position_.size()ridx exceed bound ridx= pos=opt_dense_colEXP Param: speed optimization for dense column.ColMakerTrainParamcolmaker_train_paramfmat.Info().num_row_ == position_.size()param_.sampling_method == TrainParam::kUniformOnly uniform sampling is supported, gradient-based sampling is only support by GPU Hist./home/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/transform.hUpdater `grow_colmaker` or `exact` tree method doesn't support distributed training.Grow tree with parallelization over columns.& 0N7xgboost4tree9BaseMakerEN7xgboost4tree9HistMakerEN7xgboost4tree11CQHistMakerEN7xgboost4tree23GlobalProposalHistMakerEZN7xgboost4tree11CQHistMaker10CreateHistERKSt6vectorINS_6detail20GradientPairInternalIfEESaIS5_EEPNS_7DMatrixERKS2_IjSaIjEERKNS_7RegTreeEEUlvE_*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_Egrow_histmakergrow_local_histmaker/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_histmaker.cc/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./updater_basemaker-inl.hCheck failed: tree[nid].IsLeaf()fv=, hist.size=hist[]=, hist.last=node2workindex_[nid] == static_cast(wid)sketch->temp.size < max_sizeinvalid maximum size max_size=, stemp.sizeINFO: rmax=, sum_total=, naxt_goal=, size=/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./param.hret > 0Ufid * 2 + 1 < fminmax_.size()FeatHelper fid exceed query bound fid * 2 < fminmax_.size()Check failed: param_.max_depth > 0max_depth must be larger than 0istart != hist.size/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/quantile.h check quantile stats, nbig=, n= srcsize=, maxsize=, range=, chunk=] rmin=, rmax=, wmin=, v=Check failed: nbig < nquantile: too many large chunkfi.Read(&this->size, sizeof(this->size)) == sizeof(this->size)fi.Read(this->data, this->size * sizeof(Entry)) == this->size * sizeof(Entry)sketch->temp.size <= max_sizeFinalize: invalid maximum size, max_size=, stemp.size=summary_array_.size() == sketchs_.size()offset == -2this->wspace_.rptr.size() == (fset.size() + 1) * this->qexpand_.size() + 1this->qexpand_.size() == 1Uthis->wspace_.rptr.back() == this->wspace_.cut.size()Tree constructor that uses approximate histogram construction.Tree constructor that uses approximate global of histogram construction.N7xgboost4tree10TreePrunerE*N7xgboost4treeUlvE_Eprune/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_prune.ccCheck failed: !tree[pid].IsLeaf()nid >= 1PrunerUpdatetree pruning end, extra nodes, pruned nodes, max_depth=syncTreePrunerPruner that prune the tree according to statistics.FbN7xgboost4tree17QuantileHistMaker7BuilderIdE11ExpandEntryES4_EFbN7xgboost4tree17QuantileHistMaker7BuilderIfE11ExpandEntryES4_EN7xgboost4tree17QuantileHistMakerEN7xgboost4tree17QuantileHistMaker7BuilderIfEEN7xgboost4tree17QuantileHistMaker7BuilderIdEEN7xgboost4tree16HistSynchronizerIfEEN7xgboost4tree27DistributedHistSynchronizerIfEEN7xgboost4tree13HistRowsAdderIfEEN7xgboost4tree24DistributedHistRowsAdderIfEEN7xgboost4tree21BatchHistSynchronizerIfEEN7xgboost4tree18BatchHistRowsAdderIfEEN7xgboost4tree16HistSynchronizerIdEEN7xgboost4tree27DistributedHistSynchronizerIdEEN7xgboost4tree13HistRowsAdderIdEEN7xgboost4tree24DistributedHistRowsAdderIdEEN7xgboost4tree21BatchHistSynchronizerIdEEN7xgboost4tree18BatchHistRowsAdderIdEEPFbN7xgboost4tree17QuantileHistMaker7BuilderIfE11ExpandEntryES4_EPFbN7xgboost4tree17QuantileHistMaker7BuilderIdE11ExpandEntryES4_ESt15_Sp_counted_ptrIPN7xgboost6common16PartitionBuilderILm2048EE9BlockInfoELN9__gnu_cxx12_Lock_policyE2EE*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_ESubtractionTrick/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/././../common/threading_utils.hbegin < endi < first_dimension_.size()i < ranges_.size()/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.ccCheck failed: (*p_last_tree_)[nid].IsLeaf()SyncHistograms/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./../common/row_set.helem_of_each_node_.size() == 0U/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./../common/column_matrix.h/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./../common/hist_util.hid != kMaxvector::_M_fill_insertgmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_valgmat_bin_size == kUint32BinsTypeSizebins_type_size_ == kUint32BinsTypeSizeQuantile::BuilderQuantileHistMakergrow_fast_histmaker is deprecated, use grow_quantile_histmaker instead.cut_ptr[fid] <= static_cast(std::numeric_limits::max())cut_ptr[fid + 1] <= static_cast(std::numeric_limits::max())upper_bound < static_cast(std::numeric_limits::max())SplitSiblingsCPUHistMakerTrainParamsingle_precision_histogramUse single precision to build histograms.EvaluateSplitsCheck failed: e.begin != nullptrn_left + n_right == e.Size()begin + n_left <= e.endbegin + n_left + n_right == e.end(*p_tree)[nid].LeftChild() + 1 == (*p_tree)[nid].RightChild()ApplySplitInitNewNodeBuildNodeStats/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/././../common/transform.hcpu_hist_train_param/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./updater_quantile_hist.hAttempted to load internal configuration for a model file that was generated by a previous version of XGBoost. A likely cause for this warning is that the model was saved with saveRDS() in R or pickle.dump() in Python. We strongly ADVISE AGAINST using saveRDS() or pickle.dump() so that the model remains accessible in current and upcoming XGBoost releases. Please use xgb.save() instead to preserve models for the long term. For more details and explanation, see https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.htmlCheck failed: (param_.max_depth > 0 || param_.max_leaves > 0)max_depth or max_leaves cannot be both 0 (unlimited); at least one should be a positive quantity.max_depth cannot be 0 (unlimited) when grow_policy is depthwise.InitDatarow_indices.size() + unused_rows_.size() == info.num_row_min_nbins_per_feature > 0Urow_ptr_[nid] == kMaxAddHistRowsnid < nodes_tid < nthreads_BuildLocalHistogramsnodes == targeted_hists.size()ExpandWithLossGuideUpdateGmatInitializationUpdatePredictionCacheout_preds.size() > 0Uend > beginSyncHistogramsAllreducegrow_fast_histmaker(Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram.Grow tree using quantized histogram.N7xgboost4tree13TreeRefresherEZN7xgboost4tree13TreeRefresher6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKSt6vectorIPNS_7RegTreeESaISC_EEEUlvE0_*N7xgboost4treeUlvE_Erefresh/home/runner/work/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.N7xgboost4tree11TreeSyncherE*N7xgboost4treeUlvE_ESyncher that synchronize the tree in all distributed nodes.N5rabit6engine7IEngineEN5rabit6engine13AllreduceBaseENULLrabit_tracker_urirabit_tracker_portrabit_task_idDMLC_TRACKER_URIDMLC_TRACKER_PORTDMLC_TASK_IDDMLC_ROLErabit_world_sizerabit_hadoop_moderabit_tree_reduce_minsizerabit_reduce_ring_mincountrabit_reduce_ring_mincount should be greater than 0rabit_reduce_buffer%lu%cinvalid format for %sinvalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB}DMLC_WORKER_CONNECT_RETRYrabit_bootstrap_cacherabit_debugrabit_timeoutrabit_timeout_secrabit_timeout_sec should be non negative secondrabit_enable_tcp_no_delaySocket %s Error:%scannot obtain address of %sDoes not support IPv6/home/runner/work/ml-builds/ml-builds/xgboost/rabit/src/allreduce_base.ccConnect to (failed): [] ConnectRetry connect to ip(retry time ): [SendAllReConnectLink failure 1RecvAllReConnectLink failure 2sync::Invalid tracker message, init failureReConnectLink failure 3error during send SendStrshutdownSocket::Close double close the socket or close without createFailed to shutdown due toprintworker256MBDMLC_NUM_ATTEMPTtoo large type_nbytes=%lu, buffer_size=%lu/home/runner/work/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/socket.hPoll timeoutPollReadToRingBuffer: max_size_read checkAllreduce: boundary checkbuffer size inconsistentmust assign buffer_sizeAllreduce: size checkAllreduce: boundary errorReadToRingBuffer: buffer not allocatedneed to assume rank structureAllgatherRing failedwrite ptr boundary check[%d] read_ptr boundary checkAllreduce failedBroadcast: root should be smaller than world sizeBroadcast failedtask connected to the trackerReConnectLink failure 4must keep rank to same if the node already have onetracker got overwhelemed and not able to assign correct rank got new rank 0.0.0.0TryBindHostReConnectLink fail to bind the ports specifiedGetSockErrorReConnectLink failure 5ReConnectLink failure 6ReConnectLink failure 7ReConnectLink failure 8error during send RecvStrReConnectLink failure 9ReConnectLink failure 10ReConnectLink failure 12ReConnectLink failure 13ReConnectLink failure, link rank inconsistentOverride a link that is activeReConnectLink failure 14AcceptReConnectLink failure 15ReConnectLink: bad socketSetNonBlock-1SetNonBlock-2SetKeepAlivecannot find parent in the linkcannot find prev ring in the linkcannot find next ring in the linkfailed in ReconnectLink mapred_tip_id%[^=]=%smapreduce_task_idhadoop_mode is set but cannot find mapred_task_idmapred_task_idmapred_map_tasksmapreduce_job_mapshadoop_mode is set but cannot find mapred_map_tasksRabit Module currently only work with dmlc workercan only call Init oncefail to get host namestartrabit_num_trialzrjbZ4,$ < N5rabit5c_api11ReadWrapperEN5rabit5c_api12WriteWrapperEFailed to initialize RABIT.Failed to shutdown RABIT worker.unknown data_typeDataType does not support bitwise or operationunknown enum_opnot implementedRead pickle stringthe rabit has not been initializedcannot initialize reduce handle twicemust intialize handle to call AllReduceNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS3_17RowBlockContainerImlEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS3_17RowBlockContainerIjlEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS3_17RowBlockContainerImiEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS3_17RowBlockContainerIjiEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS3_17RowBlockContainerImfEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS3_17RowBlockContainerIjfEESaIS8_EEEUlvE_vEEEESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS4_17RowBlockContainerImlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EEN4dmlc8DataIterINS_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_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS2_4data17RowBlockContainerIjfEESaIS7_EEE4InitESt8functionIFbPPS9_EESB_IFvvEEEUlvE_vEEEEZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlPPSt6vectorINS0_17RowBlockContainerImfEESaIS8_EEE_ZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS2_4data17RowBlockContainerImfEESaIS7_EEE4InitESt8functionIFbPPS9_EESB_IFvvEEEUlvE_vEEEEZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjfEEE_ZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjfEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEEZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImfEEE_ZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerImfEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEEZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjiEEE_ZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjiEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEEZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImiEEE_ZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerImiEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEEZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjlEEE_ZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerIjlEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEEZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImlEEE_ZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_4data17RowBlockContainerImlEEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS3_4data17RowBlockContainerIjfEESaIS8_EEE4InitESt8functionIFbPPSA_EESC_IFvvEEEUlvE_vEEEESaISM_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS3_4data17RowBlockContainerImfEESaIS8_EEE4InitESt8functionIFbPPSA_EESC_IFvvEEEUlvE_vEEEESaISM_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjfEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_vEEEESaISJ_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImfEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_vEEEESaISJ_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjiEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_vEEEESaISJ_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImiEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_vEEEESaISJ_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjlEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_vEEEESaISJ_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImlEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_vEEEESaISJ_ELN9__gnu_cxx12_Lock_policyE2EE/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.hcannot call ParseNext/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././parameter.h/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./././strtonum.hCheck failed: base <= 10 && base >= 2sign == true.split.part/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/uri_spec.hname_cache.size() == 1Uonly one `#` is allowed in file path for cachefile specificationCheck failed: std::getline(is, kv.first, '=')Invalid uri argument format for key in arg Check failed: std::getline(is, kv.second) for value in arg name_args.size() == 1U/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data.ccUnknown data type File 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.LibSVMParserParamlibfmIf >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.LibFMParserParamFile format.label_columnColumn index (0-based) that will put into label.delimiterDelimiter used in the csv file.weight_columnColumn index that will put into instance weights.CSVParserParam/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./row_block.hlabel.size() + 1 == offset.size()offset.back() == index.size()Check failed: offset.back() == value.size() || value.size() == 0/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/csv_parser.hparam_.format == "csv"Check failed: param_.label_column != param_.weight_column || param_.label_column < 0Must have distinct columns for labels and instance weights/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/libfm_parser.hparam_.format == "libfm"/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.hparam_.format == "libsvm"Check failed: fi->Read(&label)Bad RowBlock formatCheck failed: fi->Read(&weight)Check failed: fi->Read(&qid)Check failed: fi->Read(&field)Check failed: fi->Read(&index)Check failed: fi->Read(&value)Check failed: fi->Read(&max_field, sizeof(IndexType))Check failed: fi->Read(&max_index, sizeof(IndexType))/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.hMB read, MB/secfinish reading at /home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/disk_row_iter.hfinish reading at %g MB/secCheck failed: TryLoadCache()failed to build cache file Check failed: out->field.size() == out->index.size()Check failed: out->label.size() + 1 == out->offset.size()qid:Delimiter '' is not found in the line. Expected '' as the delimiter to separate fields.Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size()/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/././text_parser.hchunk.size != 0UFvvEN4dmlc10InputSplitEN4dmlc2io15SingleFileSplitEN4dmlc8DataIterINS_2io14InputSplitBase5ChunkEEEN4dmlc12ThreadedIterINS_2io14InputSplitBase5ChunkEEEN4dmlc2io16CachedInputSplitEN4dmlc2io18ThreadedInputSplitEZN4dmlc2io16CachedInputSplit15InitPreprocIterEvEUlPPNS0_14InputSplitBase5ChunkEE_PFvvENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEEZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlPPNS0_14InputSplitBase5ChunkEE_ZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlvE0_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlPPNS2_5ChunkEE_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlvE0_St23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS3_2io14InputSplitBase5ChunkEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_vEEEESaISJ_ELN9__gnu_cxx12_Lock_policyE2EEviewfs://Please compile with DMLC_USE_HDFS=1 to use hdfss3://http://https://Please compile with DMLC_USE_S3=1 to use S3azure:///home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io.ccPlease compile with DMLC_USE_AZURE=1 to use Azureunknown filesystem protocol hdfs:///home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/single_file_split.hInputSplit do not support writeCheck failed: part_index == 0 && num_parts == 1/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/cached_input_split.hResetPartition is not supported in CachedInputSplitBeforeFirst is not supportedCheck failed: nread == sizeof(size) has invalid cache file formatCheck failed: fi_->Read(p->begin, size) == sizestdinCheck failed: fp_ != NULLSingleFileSplit: fail to open Check failed: part < nsplitinvalid input parameter for InputSplit::Createindexed_recordioneed to pass index file to use IndexedRecordIOunknown input split type rbCheck failed: this->InitCachedIter()Failed to initialize CachedIterN4dmlc2io12LineSplitterE/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.ccCheck failed: begin != endN4dmlc2io16RecordIOSplitterE/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/recordio_split.ccCheck failed: fi->Read(&lrec, sizeof(lrec)) != 0invalid record io format(reinterpret_cast(begin) & 3UL) == 0U(reinterpret_cast(end) & 3UL) == 0UCheck failed: p >= pbegin + 2Check failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->endInvalid RecordIO Format(reinterpret_cast(chunk->begin) & 3UL) == 0U(reinterpret_cast(chunk->end) & 3UL) == 0UCheck failed: chunk->begin <= chunk->endCheck failed: cflag == 1UCheck failed: p[0] == RecordIOWriter::kMagicN4dmlc2io23IndexedRecordIOSplitterE/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.ccexpanded_list.size() == 1ulIndexedRecordIOSplitter does not support multiple index files .<~phzvphzvN4dmlc2io14InputSplitBaseESt23_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_traitsIcEELb1ELb1EEEw^$.*+?| ""//\\abf n r t v /home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/input_split_base.ccCheck failed: offset_end_ >file_offset_[file_ptr_end_]Check failed: file_ptr_end_ < files_.size()curr=,begin=,end=,fileptr=,fileoffset=offset[file offset not calculated correctly^$\.*+?()[]{}|.[\*^$.[\()*+?{|^$.[\*^$ .[\()*+?{|^$ bad regex This could due to compiler version, g++-4.9 is neededfiles_.size() != 0UCannot find any files that matches the URI pattern Check failed: files_[i].size % align_bytes == 0file do not align by bytesNULSOHSTXETXEOTENQACKalertbackspacetabnewlinevertical-tabform-feedcarriage-returnSOSIDLEDC1DC2DC3DC4NAKSYNETBCANEMSUBESCIS4IS3IS2IS1spaceexclamation-markquotation-marknumber-signdollar-signpercent-signampersandapostropheleft-parenthesisright-parenthesisasteriskplus-signcommahyphenperiodslashzerotwothreefourfivesixseveneightninecolonsemicolonless-than-signequals-signgreater-than-signquestion-markcommercial-atABCDFGHIJKMNOPQRSVWXZleft-square-bracketbackslashright-square-bracketcircumflexunderscoregrave-accentbfjuvxzleft-curly-bracketvertical-lineright-curly-brackettildeDELalnumblankcntrldigitgraphlowerpunctupperxdigitN4dmlc2io15LocalFileSystemEN4dmlc2io10FileStreamE/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/local_filesys.ccLocalFileSystem.GetPathInfo: detected symlink error: LocalFileSystem.GetPathInfo: stdoutwbCheck failed: allow_null LocalFileSystem::Open "": Check failed: !std::fseek(fp_, static_cast(pos), SEEK_SET)Check failed: std::fwrite(ptr, 1, size, fp_) == sizeFileStream.Write incompleteLocalFileSystem.ListDirectory ..N4dmlc2io10FileSystemE/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/filesystem.hlstat(path.c_str(), &sb) == 0dmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/filesys.ccCheck failed: !IsSymlink(info.path.name)Symlink not supported in TemporaryDirectoryCouldn't remove file Successfully deleted temporary directory ~TemporaryDirectory(): Could not remove temporary directory ;VȰ0H"0-;@8Fx8Jxqs@X|Ѝ(8h (P `EHP o`v}Ѐ ,`y<XعXXpغ  X@"P,ػ9F`JXL(h8(`p(h0pP@@X&'X*,<`EHXKPKXxNpPQ[l@pv08w|} `h`0@8X88@h0+H,pH/o` qH u v @wPp@xhP(8xx=8@B@`P0Ȝ@8 "#@&H(*О,P.H01`4(607h9;= @`ACءEHXHJHMNN0PhRhUأ0X[P]_ȨxfX0lةPo x{Ьx@(`H((H0HxHX@HPع8 ؊( 8Phȋ (0(8@@XHpPX`xЌ0H`x؍ 8Ph @HhȎp0H`x0؏8 8Ph8Ȑ@px(@XpБ (0@HH``xhؒ 8Ph ȓ HHp(x@(@hhxЖ 8h`#ؗ$P%8(**,P,-(/0P1xX22ؚ`=8>hp@@ЛpAB0B`HCEF80HȤ(JNPO\إx^P`Xeg(i@XiXjjkl xm@ssxu{}XXP(`h8`8خHhHH 0HxXhpxH`@ 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