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EPNS_6ParserIjiEE_ZN4dmlc4data10ParserImplIjiE4NextEv_ZN4dmlc4data12BasicRowIterIjiE4InitEPNS_6ParserIjiEE_ZN4dmlc12RowBlockIterIjiE6CreateEPKcjjS3__ZNSt6vectorIN4dmlc4data17RowBlockContainerImfEESaIS3_EE17_M_default_appendEm_ZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS0_17RowBlockContainerImfEESaIS5_EE_ZTVSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTVNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS3_17RowBlockContainerImfEESaIS8_EEEUlvE_vEEEE_ZN4dmlc4data14TextParserBaseImfE9ParseNextEPSt6vectorINS0_17RowBlockContainerImfEESaIS5_EE_ZNSt6vectorIN4dmlc4data17RowBlockContainerIjfEESaIS3_EE17_M_default_appendEm_ZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS0_17RowBlockContainerIjfEESaIS5_EE_ZTVSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTVNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS3_17RowBlockContainerIjfEESaIS8_EEEUlvE_vEEEE_ZN4dmlc4data14TextParserBaseIjfE9ParseNextEPSt6vectorINS0_17RowBlockContainerIjfEESaIS5_EE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS3_17RowBlockContainerImlEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS3_17RowBlockContainerImlEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS3_17RowBlockContainerIjlEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS3_17RowBlockContainerIjlEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS3_17RowBlockContainerImiEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS3_17RowBlockContainerImiEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS3_17RowBlockContainerIjiEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS3_17RowBlockContainerIjiEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS3_17RowBlockContainerImfEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS3_17RowBlockContainerImfEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS3_17RowBlockContainerIjfEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS3_17RowBlockContainerIjfEESaIS8_EEEUlvE_vEEEE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS4_17RowBlockContainerImlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS4_17RowBlockContainerImlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__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_ZTSN4dmlc12ScopedThreadE_ZTIN4dmlc12ScopedThreadE_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_ZTSN4dmlc4data11LibFMParserIm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H$It$0H9t( H$`H;|$t H9l$IH|$LuHpH$`L}MMM ILt$x@Ht$01L)CHT$xHH$`H$pLLvLt$xL$`s@IL$I$MLL$ LsC1Ls0L$Ls L$MMtMuH=@IL$IMM@H{PLk(C+L$H{@L$LLM H=#nfDHt$8I|$ 1BL$HH$L$HLQH$L$@Ht$(I|$@1AHH$H$H$HLH$H$@H$H$H`H9HtoHSL$hHL$`HT$ MMtbMu]H=&qIL$IMHLkHB)H$H`H$fDIL$IMHt$ L{0LkB.L$L{ L$MMtMuH=q@IL$IMM8HCPLk(C*L$HC@L$LLMH=NfDAL$`$p_AuMt$0@$fEUIT$PD$fHt$@H{@1?H$HHC@HsPLLL$LC@iH$H{ 1M?H$HHC HS0LLL$L[ fDH$1H?L$HHLkLLYL$L fE7IDsPAMC0QELL$ DCfDH$H{ 1>L$HHC LK0LLL$LS fDH$H{@1=>L$HHC@L[PLLL$HK@fDH$1H=L$HHLsLLIL$H3#fLLAHt$ KA>M@{0HE>HD{PxL|LGHH|$XLs9hfDL,LH,HLHHl$hHHLLT$(Lk0Hk(Lk Mr Mz(LLtMu H=IL|$pwQIWMLu\H|$(L{(B8HCPHC@Ho@LwHHLHH=NHt$pH{ 19HxMVHMf(MzM9LI<$IHLHM9HHtlHtYHtFHt3Ht Ht I<$IoI<$IbI<$IUI<$IHI<$I;I<$I.I<$I!M9vXI<$I@I|$I|$I|$I|$I|$I|$I|$M9wI>H([]A\A]A^A_ML;,$H<$MUPL)H`HL$I}@AL9tsI} M]0L9taI}IEH9tOI]`H9$QMIt{ItHMWMOMt$(LI|$ML$HMMT$8I|$HMD$ HM\$@I)KLmHLIL$0H[]A\A]A^A_DID$@HpI9MI>IIIIAI9Mt}ItfItTItBIt0ItIt I>I\I>IPI>IDI>I8I>I,I>I I>II9sPI>I@I~I~I~I~I~I~I~I9rI" LZI<$I$ID$IL{)f.AWAVAUATIUSHH8HoHHHWdH%(HD$(1HH)HHH)HHEHk0HtnLeMuLeM}Ld$MMMH=Of.ILl$ I'MI LmHC)HkHHD$(dH3%(LULSHL]ML[8L[0Lc@cH8[]A\A]A^A_@ILt$IML\$L}0LuC3Me(L} Mu LLtMuH=tILd$I7MLLe(B'H}PH}@Mu@MmHLLMH=YfHw(HH)HLwLgO6L9mHHlIL9IH<L[HHs(IM)IIISN4H)HHHH;L;HkILs(IKl&HkHHSHHS HuHs8HHs@fDHt$ H}@1 (LD$ HHE@LEPLLuLl$ LM@Ht$1H'LT$HHELULL6Lt$L]Ht$H} 1'HT$HHE HU0LLLd$H} 4L)HL4L9HUH)HHHLIDEL\$DM}fDALE0fE>ID}P*fDLXSInIYHUIH)HHH8LH)L%fLLH} I9tH}H9|$tLHH[HH{I+L$HHbasic_string::_M_construct null not valid%s: __pos (which is %zu) > this->size() (which is %zu)/__w/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/utils.hread can not have position excceed buffer lengthwrite position exceed fixed buffer size/__w/ml-builds/ml-builds/xgboost/src/c_api/../data/proxy_dmatrix.hSlicing DMatrix is not supported for Proxy DMatrix./__w/ml-builds/ml-builds/xgboost/src/c_api/../data/adapter.h/__w/ml-builds/ml-builds/xgboost/src/c_api/../common/common.hXGBoost version not compiled with GPU support./__w/ml-builds/ml-builds/xgboost/src/c_api/c_api.ccDMatrix/Booster has not been initialized or has already been disposed.Current DMatrix type does not support set data./__w/ml-builds/ml-builds/xgboost/src/c_api/../data/array_interface.h Please verify the `__cuda_array_interface__/__array_interface__' of your input data complies to: https://docs.scipy.org/doc/numpy/reference/arrays.interface.htmlbinary saving only supported by SimpleDMatrixCheck failed: type >= 1 && type <= 4XGDMatrixSetGroup is deprecated, use `XGDMatrixSetUIntInfo` instead.Unknown field for Booster feature info:/__w/ml-builds/ml-builds/xgboost/src/c_api/c_api_utils.hstd::accumulate(shape.cbegin(), shape.cend(), 1, std::multiplies<>{}) == chunksize * rows/__w/ml-builds/ml-builds/xgboost/include/xgboost/json.hMissing `version' field for array interfaceOnly version <= 3 of `__cuda_array_interface__/__array_interface__' are supported.Missing `typestr' field for array interfaceCheck failed: typestr.size() == 3 || typestr.size() == 4`typestr' should be of format .Missing `shape' field for array interfaceMissing `data' field for array interfacevector::_M_range_check: __n (which is %zu) >= this->size() (which is %zu)basic_string::at: __n (which is %zu) >= this->size() (which is %zu)mask with bitfield type should be of 1 byte per bitfield.mask with integer type should be of 1 byte per integer.mask must be of integer type or bit field type.get(strides.at(0)) == type_lengthOnly 1-D and 2-D arrays are supported.shape.first * shape.second == 0Empty data with non-zero shape.Shape of bit mask doesn't match data shape. XGBoost doesn't support internal broadcasting.Check failed: array.find("mask") == array.cend()Masked array is not yet supported.get(jinterface).size() == 1Check failed: num_rows == 1 || num_cols == 1Array should be a vector instead of matrix.DMatrix has not been initialized or has already been disposed.Check failed: iteration_end == 0Only one of the `ntree_limit` or `iteration_range` can be specified.`ntree_limit` is deprecated, use `iteration_range` instead.get(config["cache_id"]) == 0custom_feature_names.size() == n_featuresIncorrect number of feature names.feature_names.size() == n_featuresfeature_types.size() == n_featuresIncorrect number of feature types./__w/ml-builds/ml-builds/xgboost/include/xgboost/feature_map.hfid == static_cast(names_.size())unknown feature type, use i for indicator and q for quantityfeature_map.Size() == n_featuresFeatureMap feature index exceed boundfeatures.size() <= scores.size()scores.size() % features.size() == 0ulfeatures.size() == scores.size()XGBoost distributed mode detected, static_cast*>(handle) ->get() ->Info() .group_ptr_.size() == 0Uslice does not support group structureCheck failed: ec == std::errc()Check failed: columns_ == data::kAdapterUnknownSize || columns_ == batch.columnsNumber of columns between batches changed from %02d:%02d:%02d] : basic_string::appendOnly %d dimensional array is valid.Stack trace: _Z +basic_string::basic_string [bt] () DMLC_LOG_STACK_TRACE_DEPTH%zuCheck failed: at_first_Cannot reset IteratorAdapterCheck failed: p_mCheck failed: mBit fieldBooleanIntegerUnsigned integerFloating pointComplex floating pointTimedeltaDatetimeObjectStringUnicodeOtherInvalid type code: in `typestr' of input array. Or open an issue.- is not supported.Check failed: p_outmap::at vs. vector::_M_default_appendNot implemented.feature_namefeature_typejsonCheck failed: chunksize == groupsUnknown prediction type:Invalid cast, from gradient_boosterlearnergblinearnum_parallel_treegbtree_train_paramstoiUnknown booster:streamtypestrEmpty data passed in.maskj_shape.size() == 1type_length == 1stridesstrides.size() == 1Memory should be contigious.j_shape.size() == 2n_bits == num_rowsj_strides.size() <= 2Check failed: validInvalid strides in array. strides: (), shape: (Column: iteration_beginiteration_endntree_limittrainingstrict_shapeInvalid missing value: cache_idCache ID is not supported yetCheck failed: p_predtstr.size() > 2str[0] == '{'%lufloattextimportance_typefeature_mapfeature_namesidx < names_.size()will split data among workersautocache_prefixnthread__', Possible Arguments: ---------------- Cannot find argument 'Check failed: e%ldUnknown global parameters: { vector::_M_range_insertx8xxxXxxxxxxxxxxxxxxxxxxxx8xxxxxxXp,,St11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EESt12__shared_ptrIN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt12__shared_ptrIN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EEN4dmlc5ErrorEN4dmlc6StreamEN4dmlc10SeekStreamEN4dmlc7istream5InBufEN4dmlc7istreamEN4dmlc10ParamErrorEN4dmlc9parameter16FieldAccessEntryEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIiEEiEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIiEEiEEN4dmlc9parameter10FieldEntryIiEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIbEEbEEN4dmlc9parameter10FieldEntryIbEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIfEEfEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIfEEfEEN4dmlc9parameter10FieldEntryIfEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIdEEdEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIdEEdEEN4dmlc9parameter10FieldEntryIdEEN5rabit5utils19MemoryFixSizeBufferEN5rabit5utils18MemoryBufferStreamEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIlEElEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIlEElEEN4dmlc9parameter10FieldEntryIlEEN7xgboost5ValueEN4dmlc8DataIterIN7xgboost4data15CSRAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_15CSRAdapterBatchEEEN7xgboost4data10CSRAdapterEN4dmlc8DataIterIN7xgboost4data17DenseAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_17DenseAdapterBatchEEEN7xgboost4data12DenseAdapterEN4dmlc8DataIterIN7xgboost4data17ArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_17ArrayAdapterBatchEEEN7xgboost4data12ArrayAdapterEN4dmlc8DataIterIN7xgboost4data20CSRArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_20CSRArrayAdapterBatchEEEN7xgboost4data15CSRArrayAdapterEN4dmlc8DataIterIN7xgboost4data15CSCAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_15CSCAdapterBatchEEEN7xgboost4data10CSCAdapterEN4dmlc8DataIterIN7xgboost4data21DataTableAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_21DataTableAdapterBatchEEEN7xgboost4data16DataTableAdapterEN4dmlc8DataIterIN7xgboost4data16FileAdapterBatchEEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIjEEjEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIjEEjEEN4dmlc9parameter10FieldEntryIjEEN7xgboost4data12DMatrixProxyEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryImEEmEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryImEEmEEN4dmlc9parameter10FieldEntryImEEN7xgboost4data15IteratorAdapterIPvFiS2_PFiS2_15XGBoostBatchCSRES2_ES3_EESt15_Sp_counted_ptrIPN7xgboost7DMatrixELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data12DMatrixProxyELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_10SparsePageEEELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_7CSCPageEEELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_13SortedCSCPageEEELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_11EllpackPageEEELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_16GHistIndexMatrixEEELN9__gnu_cxx12_Lock_policyE2EESt10shared_ptrIN7xgboost4data12ArrayAdapterEESt10shared_ptrIN7xgboost4data15CSRArrayAdapterEE?C@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!00010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899Check failed: falsesibling.size() == sizeparent.size() == size/__w/ml-builds/ml-builds/xgboost/src/common/hist_util.ccvector::_M_fill_insertSize() == other.Size()Size() == other.size()/__w/ml-builds/ml-builds/xgboost/src/common/host_device_vector.ccbasic_string::substrCheck failed: outfile://Opening Not implementedpointer_ <= buffer_.size()/__w/ml-builds/ml-builds/xgboost/src/common/io.cc/__w/ml-builds/ml-builds/xgboost/src/common/io.hN7xgboost6common16PeekableInStreamEN7xgboost6common15FixedSizeStreamE/__w/ml-builds/ml-builds/xgboost/src/common/json.cc can not be indexed by Integer. can not be indexed by string. Please try obtaining std::string first.Check failed: ret.ec == std::errc()vector::_M_emplace_back_auxArrayNullObject of type , around character position: , "beg <= size_\n\0", got: "EOF"\0"Expecting digit \\\"\b\f\r\t\u%04xch != -1cursor_.Pos(): raw_str_.size():к8`N7xgboost10JsonStringEN7xgboost9JsonArrayEN7xgboost10JsonObjectEN7xgboost10JsonNumberEN7xgboost11JsonIntegerEN7xgboost8JsonNullEN7xgboost11JsonBooleanEN7xgboost10JsonReaderEN7xgboost10JsonWriterE/__w/ml-builds/ml-builds/xgboost/src/common/quantile.cc/__w/ml-builds/ml-builds/xgboost/src/common/quantile.hCheck failed: a.data && reduced[fidx].dataCheck failed: size <= sa.size + sb.sizeCheck failed: worker_feature.data()hessian.size() == info.num_row_group_ptr.back() == hessian.size()weights.size() == info.num_row_Check failed: nlevel <= std::max(static_cast(1), static_cast(limit_size * eps))Number of columns differs across workerscuts->cut_values_.HostVector().size() <= std::numeric_limits::max()cut_size > cuts->cut_ptrs_.HostVector().back()src.size == 0this->size == 0Check failed: a.datamingap=, maxgap=, wgap=bug in combinecount <= total_entriesn_threads_ >= 1sketches_.size() == n_columnsgroup_ptr.size() >= 2group_ptr.back() == n_samplesinvalid init parameterworker_segments.size() >= 1num_cuts.size() == 0n_columns == sketches_.size()columns_size_.size() != 0Check failed: reduced[i].dataMakeCutsAllReducePushRowPageHostSketchContainer? AA_>?features.size() > 0/__w/ml-builds/ml-builds/xgboost/src/common/random.harray.size() == weights.size()/__w/ml-builds/ml-builds/xgboost/src/common/random.cc@@0St19_Sp_make_shared_tagSt23_Sp_counted_ptr_inplaceIN7xgboost16HostDeviceVectorIjEESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE75/value for Parameter exceed bound [ should be greater equal to should be smaller equal to Required parameter is not presentedInvalid Parameter format for expect but value=' optional, default=, requiredInvalid Input: '', valid values are: *p == ')'Invalid NAN literalpos <= value.length()Out of range value for , value='Out of range valueEnum exisit!) Enums: ), key /__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./parameter.henum_back_map_.count(value) != 0UValue not found in enum declared/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././strtonum.hNo conversion could be performedSome trailing characters could not be parsed: ' has already been registered in N4dmlc9parameter10FieldEntryIN7xgboost6common27ProbabilityDistributionTypeEEEY@v? LTimer for calls @ us======== Monitor ( ======== did not get stopped properly..AIncorrect version format found in binary file. Binary file from XGBoost < 1.0.0 is no longer supported. Please generate it again./__w/ml-builds/ml-builds/xgboost/src/common/version.ccfi->Read(&read[0], verstr.size()) == verstr.size()Check failed: fi->Read(&major)Check failed: fi->Read(&minor)Check failed: fi->Read(&patch)Invaid version format in loaded JSON object: /__w/ml-builds/ml-builds/xgboost/src/data/data.ccUnknown data type for getting meta info.Check failed: v.DeviceIdx() == GenericParameter::kCpuId || device == GenericParameter::kCpuId || v.DeviceIdx() == deviceData is resided on a different device than `gpu_id`. /__w/ml-builds/ml-builds/xgboost/src/data/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.hCheck failed: lock_.try_lock()Multiple threads attempting to use Sparse DMatrix./__w/ml-builds/ml-builds/xgboost/src/data/file_iterator.h/__w/ml-builds/ml-builds/xgboost/src/data/../data/adapter.h/__w/ml-builds/ml-builds/xgboost/src/data/../data/iterative_device_dmatrix.hSlicing DMatrix is not supported for Device DMatrix./__w/ml-builds/ml-builds/xgboost/src/data/../data/simple_batch_iterator.hCheck failed: page_ != nullptrself_offset.size() == other_offset.size()this->base_margin_.Size() % this->num_row_ == 0Incorrect size of base margin vector./__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_writer.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./././any.hCheck failed: type_ != nullptrCheck failed: *(type_->ptype_info) == typeid(T)All feature_types must be one of {int, float, i, q, c}. must be equal to number of columns.group_ptr_.size() == weights_.Size() + 1Size of weights must equal to number of groups when ranking group is used.Invalid group structure. Number of rows obtained from groups doesn't equal to actual number of rows given by data.Size of weights must equal to number of rows.Size of labels must equal to number of rows.labels_lower_bound_.Size() == num_row_Size of label_lower_bound must equal to number of rows.feature_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.Check failed: fmt->Read(page.get(), fi.get())key >= builder_base_row_offsetfetch_it < cache_info_->offset.size()std::count_if(ring_->cbegin(), ring_->cend(), [](auto const &f) { return f.valid(); }) == n_prefetch_batchesSparse DMatrix assumes forward iteration.Label contains NaN, infinity or a value too large.Weights must be positive values.`qid` must be sorted in non-decreasing order along with data.Feature weight must be greater than 0.this->num_col_ == that.num_col_Number of columns must be consistent across batches.transpose.offset.Size() == num_columns + 1Input data contains `inf` or `nan`/__w/ml-builds/ml-builds/xgboost/src/data/../data/proxy_dmatrix.hCheck failed: !cache_info_->writtenthis->count_ == this->n_batches_source_->Iter() == this->count_Check failed: strm->Read(&name)Check failed: strm->Read(&type_val)Check failed: type == expected_typeCheck failed: strm->Read(&is_scalar)Check failed: strm->Read(field)Check failed: strm->Read(&shape.first)Check failed: strm->Read(&shape.second)Number of columns is expected to be 1.Binary DMatrix generated by XGBoost: Please process and save your data in current version: Check failed: fi->Read(&num_field)MetaInfo: insufficient number of fields (expected at least fields, but the binary file only contains MetaInfo: the given binary file contains extra fields which will be ignored.cache_file.find('#') == std::string::nposOnly one `#` is allowed in file path for cache file specification.No format parameter is provided in input uri, but found file extension: Consider providing a uri parameter: filename?format=No format parameter is provided in input uri. Choosing default parser in dmlc-core. Consider providing a uri parameter like: filename?format=csvlabel_lower_boundlabel_upper_boundfeature_weightsUnknown float field name: group_ptrUnknown uint32 field name: Device that data is on: `gpu_id` for XGBoost: Check failed: !type_.empty()float32float64bool8int32int8int16int64Unknown data table type.Check failed: page_std::future_error: self_data.size(): other_data.size(): beg <= data.size()ptr < offset.size()Check failed: parser_qidnum_rownum_colnum_nonzerolabelslabels_lower_boundlabels_upper_boundfeature_typesfield_cnt == kNumFieldWrong number of fieldsUnknown feature info: format.front() == '.'Unknown format type The any container is empty requested=The stored type mismatch stored=size == this->num_col_Length of Unknown feature info name: group_ptr_.back() == num_row_weights_.Size() == num_row_labels_.Size() == num_row_fi->Tell() == offsetCheck failed: !at_end_n_prefetch_batches > 0total batches:Unknown data typeCheck failed: non_decUnknown key for MetaInfo: that.group_ptr_.size() != 0nthread == 1Unknown type: Check failed: proxy_count_ == n_batches_this->count_ >= 1MetaInfo: Invalid format. name == expected_name Expected field: , got: Expected field of type: got field type: Check failed: is_scalarExpected field to be a scalar; got a vectorCheck failed: !is_scalar to be a vector; got a scalarshape.second == 1major == 1 is no longer supported. again.MetaInfo: invalid formatnum_field >= expectedfields.) matrix with entries loaded from .rXGBOOST_TEST_NPARTLoad part of data parts.group groups are loaded from .base_margin base_margin are loaded from .weight weights are loaded from csvlibsvm . Encountered parser error: `@0,L 0Un_threads >= 1row_ptr.size() == 0/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index.h/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index.ccbatch_size < offset_vec.size()curent_bin_size == common::kUint32BinsTypeSize/__w/ml-builds/ml-builds/xgboost/include/xgboost/data.hCheck failed: impl_ != nullptr/__w/ml-builds/ml-builds/xgboost/src/data/../common/hist_util.hCheck failed: binTypeSize == kUint8BinsTypeSize || binTypeSize == kUint16BinsTypeSize || binTypeSize == kUint32BinsTypeSizeRaw GHistIndex binary data format.N7xgboost4data16SparsePageFormatINS_16GHistIndexMatrixEEEN7xgboost4data19GHistIndexRawFormatE*N7xgboost4dataUlvE_E/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././any.h/__w/ml-builds/ml-builds/xgboost/src/data/proxy_dmatrix.h/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index_page_source.cccuts_.Values().size() != 0N7xgboost17BatchIteratorImplINS_16GHistIndexMatrixEEEN7xgboost4data20SparsePageSourceImplINS_16GHistIndexMatrixEEEN7xgboost4data18PageSourceIncMixInINS_16GHistIndexMatrixEEEN7xgboost4data23GradientIndexPageSourceENSt13__future_base7_ResultISt10shared_ptrIN7xgboost16GHistIndexMatrixEEEENSt13__future_base17_Async_state_implISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS2_16GHistIndexMatrixEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS5_EEENSt13__future_base15_Deferred_stateISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS2_16GHistIndexMatrixEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS5_EEESt15_Sp_counted_ptrIPN7xgboost16GHistIndexMatrixELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost16GHistIndexMatrixESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base17_Async_state_implISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS3_16GHistIndexMatrixEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS6_EEESaISD_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base15_Deferred_stateISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS3_16GHistIndexMatrixEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS6_EEESaISD_ELN9__gnu_cxx12_Lock_policyE2EENSt6thread5_ImplISt12_Bind_simpleIFZNSt13__future_base17_Async_state_implIS1_IFZN7xgboost4data20SparsePageSourceImplINS4_16GHistIndexMatrixEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS7_EEC4EOSB_EUlvE_vEEEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultISt10shared_ptrIN7xgboost16GHistIndexMatrixEEEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFZNS4_4data20SparsePageSourceImplIS5_E9ReadCacheEvEUlvE_vEES6_EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZNSt13__future_base17_Async_state_implIS2_IFZN7xgboost4data20SparsePageSourceImplINS5_16GHistIndexMatrixEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS8_EEC4EOSC_EUlvE_vEEEESaISK_ELN9__gnu_cxx12_Lock_policyE2EE/__w/ml-builds/ml-builds/xgboost/src/data/array_interface.h/__w/ml-builds/ml-builds/xgboost/src/data/proxy_dmatrix.ccCheck failed: on_hostNot implemented on device./__w/ml-builds/ml-builds/xgboost/src/data/adapter.h/__w/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.h/__w/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.ccCheck failed: param != BatchParam{}Batch parameter is not initialized.Check failed: in_stream->Read(&tmagic)invalid format, magic number mismatchCheck failed: (std::is_same::value)batch_param_.hess.data() == param.hess.data()param.gpu_id >= 0param.max_bin >= 2invalid input file formattmagic == kMagicExpecting CSCAdapterparam.gpu_id == -1N7xgboost4data13SimpleDMatrixEN7xgboost17BatchIteratorImplINS_10SparsePageEEEN7xgboost4data23SimpleBatchIteratorImplINS_10SparsePageEEEN7xgboost17BatchIteratorImplINS_7CSCPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_7CSCPageEEEN7xgboost17BatchIteratorImplINS_13SortedCSCPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_13SortedCSCPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_16GHistIndexMatrixEEESt15_Sp_counted_ptrIPN7xgboost7CSCPageELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost13SortedCSCPageELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost11EllpackPageELN9__gnu_cxx12_Lock_policyE2EE/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_dmatrix.hSlicing DMatrix is not supported for external memory./__w/ml-builds/ml-builds/xgboost/src/data/./../common/common.hCouldn't remove external memory cache file ; you may want to remove it manually/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_writer.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././././any.h/__w/ml-builds/ml-builds/xgboost/src/data/./proxy_dmatrix.hthis->page_->Size() == n_features_this->page_->data.Size() == csr->data.Size()/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.ccCheck failed: sparse_page_source_Check failed: ghist_index_source_Check failed: kv.secondMake cache:.row.pageCheck failed: proxy_handleInvalid proxy handle.iter_.Next() == 1Must have at least 1 batch.DMatrix-rinfo_.num_col_ != 0this->Info().num_col_ != 0.sorted.col.page.gradient_index.pagecuts.Values().size() != 0N7xgboost4data20SparsePageSourceImplINS_10SparsePageEEEN7xgboost4data16SparsePageSourceEN7xgboost4data20SparsePageSourceImplINS_7CSCPageEEEN7xgboost4data18PageSourceIncMixInINS_7CSCPageEEEN7xgboost4data13CSCPageSourceEN7xgboost4data20SparsePageSourceImplINS_13SortedCSCPageEEEN7xgboost4data18PageSourceIncMixInINS_13SortedCSCPageEEEN7xgboost4data19SortedCSCPageSourceEN7xgboost4data17SparsePageDMatrixENSt13__future_base7_ResultISt10shared_ptrIN7xgboost7CSCPageEEEENSt13__future_base7_ResultISt10shared_ptrIN7xgboost13SortedCSCPageEEEENSt13__future_base17_Async_state_implISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS2_7CSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS5_EEENSt13__future_base15_Deferred_stateISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS2_7CSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS5_EEENSt13__future_base17_Async_state_implISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS2_13SortedCSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS5_EEENSt13__future_base15_Deferred_stateISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS2_13SortedCSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS5_EEESt15_Sp_counted_ptrIPN7xgboost4data5CacheELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data23GradientIndexPageSourceELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data16SparsePageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data13CSCPageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data19SortedCSCPageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost7CSCPageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost13SortedCSCPageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base17_Async_state_implISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS3_7CSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS6_EEESaISD_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base15_Deferred_stateISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS3_7CSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS6_EEESaISD_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base17_Async_state_implISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS3_13SortedCSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS6_EEESaISD_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base15_Deferred_stateISt12_Bind_simpleIFZN7xgboost4data20SparsePageSourceImplINS3_13SortedCSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS6_EEESaISD_ELN9__gnu_cxx12_Lock_policyE2EENSt6thread5_ImplISt12_Bind_simpleIFZNSt13__future_base17_Async_state_implIS1_IFZN7xgboost4data20SparsePageSourceImplINS4_7CSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS7_EEC4EOSB_EUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZNSt13__future_base17_Async_state_implIS1_IFZN7xgboost4data20SparsePageSourceImplINS4_13SortedCSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS7_EEC4EOSB_EUlvE_vEEEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultISt10shared_ptrIN7xgboost7CSCPageEEEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFZNS4_4data20SparsePageSourceImplIS5_E9ReadCacheEvEUlvE_vEES6_EENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultISt10shared_ptrIN7xgboost13SortedCSCPageEEEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFZNS4_4data20SparsePageSourceImplIS5_E9ReadCacheEvEUlvE_vEES6_EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZNSt13__future_base17_Async_state_implIS2_IFZN7xgboost4data20SparsePageSourceImplINS5_7CSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS8_EEC4EOSC_EUlvE_vEEEESaISK_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZNSt13__future_base17_Async_state_implIS2_IFZN7xgboost4data20SparsePageSourceImplINS5_13SortedCSCPageEE9ReadCacheEvEUlvE_vEESt10shared_ptrIS8_EEC4EOSC_EUlvE_vEEEESaISK_ELN9__gnu_cxx12_Lock_policyE2EECheck failed: page.offset.Size() != 0 && offset_vec[0] == 0/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_raw_format.ccoffset_vec.back() == page.data.Size()n_bytes == (page->data).Size() * sizeof(Entry)Raw binary data format.page->offset.Size() != 0UInvalid SparsePage fileN7xgboost4data16SparsePageFormatINS_10SparsePageEEEN7xgboost4data19SparsePageRawFormatINS_10SparsePageEEEN7xgboost4data16SparsePageFormatINS_7CSCPageEEEN7xgboost4data19SparsePageRawFormatINS_7CSCPageEEEN7xgboost4data16SparsePageFormatINS_13SortedCSCPageEEEN7xgboost4data19SparsePageRawFormatINS_13SortedCSCPageEEE*N7xgboost4dataUlvE_E*N7xgboost4dataUlvE0_E*N7xgboost4dataUlvE1_Egpu_coord_descentmodelDoBoostlayer_begin == 0layer_end == 0PredictBatchInternalPredictBatch { "bias": [ ], "weight": [ ] }bias: weight: Model is not initializedimportance_type == "weight"shotguntoleranceMaximum rows per batch.max_row_perbatchlong (non-negative)GBLinearTrainParamGBLineargblinear_train_paramCheck failed: this->updater_/__w/ml-builds/ml-builds/xgboost/src/gbm/gblinear.ccgblinear does not support prediction of leaf index/__w/ml-builds/ml-builds/xgboost/include/xgboost/gbm.hInplace predict is not supported by current booster.Slice is not supported by current booster./__w/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.hfi->Read(¶m_, sizeof(param_)) == sizeof(param_)Linear booster does not support prediction range.base_margin.size() == nsize * ngroup/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.hget(in["name"]) == "gblinear"Check failed: !model_.weight.empty()gblinear only has `weight` defined for feature importance./__w/ml-builds/ml-builds/xgboost/include/xgboost/linalg.hvec->size() == shape[0] * shape[1]Update algorithm for linear model. One of shotgun/coord_descentStop if largest weight update is smaller than this number.Loading configuration on a CPU only machine. Changing updater to `coord_descent`./__w/ml-builds/ml-builds/xgboost/src/gbm/../common/common.hLinear booster, implement generalized linear model.N4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEES8_EEN4dmlc9parameter10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEEN7xgboost5ModelEN7xgboost12ConfigurableEN7xgboost15GradientBoosterEN7xgboost3gbm8GBLinearE*N7xgboost3gbmUlPKNS_17LearnerModelParamEE_EN7xgboost3gbm13GBLinearModelEUnknown gbm type /__w/ml-builds/ml-builds/xgboost/src/gbm/gbm.cc/__w/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'.Tree method is selected to be 'hist', which uses a single updater grow_quantile_histmaker.XGBoost version not compiled with OneAPI support.Data is on CUDA device, but XGBoost is not compiled with CUDA support./__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree.hp_out_preds->predictions.Size() == predts.predictions.Size()Unsupported data type for inplace predict.predts.predictions.Size() == out_preds->predictions.Size()tparam_.num_parallel_tree != 0model_.learner_model_param->num_output_group != 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.tree_end <= model_.trees.size()ups.size() == updaters_.size() mismatched updater sequence. get(in["name"]) == "gbtree"get(in["name"]) == "dart"this->model_.learner_model_param->num_feature != 0this->model_.trees_to_update.size() == this->model_.trees.size() trees remain. Slice the model before making update if you only want to update a portion of trees.Check failed: p_dart->weight_drop_.empty()Number of features used for training and prediction.Reserved option for vector tree.Number of parallel trees constructed during each iteration. This option is used to support boosted random forest.Whether to run the normal boosting process that creates new trees, or to update the trees in an existing model.Choice of tree construction method.Different types of sampling algorithm.Different types of normalization algorithm.Fraction of trees to drop during the dropout.Whether at least one tree should always be dropped during the dropout.Probability of skipping the dropout during a boosting iteration.Learning rate(step size) of update.Check failed: !updaters_.front()->CanModifyTree()can not be used to create new trees. Set `process_type` to `update` if you want to update existing trees.Check failed: up->CanModifyTree()can not be used to modify existing trees. Set `process_type` to `default` if you want to build new trees.model_.trees.size() < model_.trees_to_update.size()No more tree left for updating. For updating existing trees, boosting rounds can not exceed previous training roundsgpair->Size() == p_fmat->Info().num_row_Mismatching size between number of rows from input data and size of gradient vector.Unknown feature importance type, expected one of: {"weight", "total_gain", "total_cover", "gain", "cover"}, got: DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.Check failed: this->configured_Check failed: tparam_.GetInitialised()in_gpair->Size() % ngroup == 0Umust have exactly ngroup * nrow gpairsLoading 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.Tree booster, gradient boosted trees.Using tree method: grow_histmaker,prunegrow_colmaker,prunegrow_quantile_histmakergrow_gpu_histUnknown tree_method () detectedCheck failed: configured_Check failed: cpu_predictor_weight_droptree_begin <= tree_endCheck failed: predictori >= p_out_preds->versioncpu_predictorgpu_predictorCheck failed: successCurrent Predictor: tree_begin == 0out_preds->version == 0Invalid number of trees.CommitModelInternal Error: Specified updaters: Actual updaters: Check failed: p_gbtreelayer_trees != 0layer_end > layer_beginstep >= 1Not all trees are updated, in_it < tree_endCheck failed: p_dartdrop trees, weight = num_treessize_leaf_vectorGBTreeModelParam has not been registered in Alias Tree updater sequence.updater_sequpdatedefaultprocess_typePredictor algorithm typeoneapi_predictorexactapproxtree_methodGBTreeTrainParamweighteduniformsample_typeforestnormalize_typerate_dropone_dropbooleanskip_droplearning_rateetaDartTrainParamUpdater: `` total_gaintotal_coverGBTreeUsing updaters: BoostNewTreesngroup != 0specified_updaterdart_train_paramvector::reserveTree booster, dart.0<<<<;X<*N7xgboost3gbmUlPKNS_17LearnerModelParamEE_E*N7xgboost3gbmUlPKNS_17LearnerModelParamEE0_EN4dmlc9parameter10FieldEntryIN7xgboost10TreeMethodEEEN4dmlc9parameter10FieldEntryIN7xgboost15TreeProcessTypeEEEN4dmlc9parameter10FieldEntryIN7xgboost13PredictorTypeEEEN7xgboost3gbm6GBTreeEN7xgboost3gbm4DartE?A;GBTree: invalid model file/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.ccparam.num_trees == static_cast(trees.size())fi->Read(¶m, sizeof(param)) == sizeof(param)fi->Read(dmlc::BeginPtr(tree_info), sizeof(int32_t) * param.num_trees) == sizeof(int32_t) * param.num_treesparam.num_trees == static_cast(trees.size())N7xgboost3gbm11GBTreeModelE/__w/ml-builds/ml-builds/xgboost/src/learner.ccCheck 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., the default evaluation metric '. Explicitly set eval_metric if you'd like to restore the old behavior.Call Configure before saving model.learner_model_param_.num_feature == p_fmat->Info().num_col_Number of columns does not match number of features in booster.learner_model_param_.num_feature >= p_fmat->Info().num_col_Predict must happen after Load or configurationPerform one kind of prediction at a time.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.Random number seed during training.Seed PRNG determnisticly via iterator number, this option will be switched on automatically on distributed mode.The primary GPU device ordinal.Fail with error when gpu_id is invalid.Enable checking whether parameters are used or not.Data split mode for distributed training.Flag to disable default metric. Set to >0 to disableGradient booster used for training.Objective function used for obtaining gradient.Check failed: !matrix.second.ref.expired()num_col <= static_cast(std::numeric_limits::max())Unfortunately, XGBoost does not support data matrices with 0 feature is supplied. Are you using raw Booster interface? } might not be used. This could be a false alarm, with some parameters getting used by language bindings but then being mistakenly passed down to XGBoost core, or some parameter actually being used but getting flagged wrongly here. Please open an issue if you find any such cases. this->learner_model_param_.num_feature != 0out_impl->learner_model_param_.num_feature == this->learner_model_param_.num_featureout_impl->learner_model_param_.num_feature != 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)Base64 format is no longer supported in brick.fi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_)BoostLearner: wrong model formatCheck failed: fi->Read(&tparam_.objective)Check failed: fi->Read(&tparam_.booster)Loading model from XGBoost < 1.0.0, consider saving it again for improved compatibilityStarting in XGBoost used with the objective '' was changed from '' to 'Configbase_scorenum_featurenum_classlearner_model_paramobjectiveattributesEmpty dataset at worker: EvalOneIter1.3.0binary:logitraw1.4.0aucmulti:softmaxmulti:softprobmloglossmerrorCheck failed: gbm_ != nullptrbinary:logisticUpdateOneIterPredictRawPredictionsGetGradientGradientsmultiple_predictions <= 1Global bias of the model.int (non-negative)LearnerModelParamLegacyseedlongrandom_stateseed_per_iterationNumber of threads to use.n_jobsfail_on_invalid_gpu_idvalidate_parametersGenericParameterdsplitdisable_default_eval_metricreg:squarederrorLearnerTrainParamCheck failed: matrix.first features or greatermparam_.num_feature != 0num_output_groupcount:poisson0.7learner_train_parammetricsgeneric_paramBoostOneIterCheck failed: IsA(in)Learnernum_roundCONFIG-offset:Unsupported prediction type:Invalid parameter "" contains whitespace. Parameters: { ", Configure;binfbegin_layer >= 0best_iterationbest_scoresz > 0bs64header != "bs64"fp.Read(&header[0], 4) == 4USAVED_PARAM_count_poisson_max_delta_stepmulti:N4dmlc12SerializableEN7xgboost7LearnerEN4dmlc9parameter10FieldEntryIN7xgboost13DataSplitModeEEEN7xgboost20LearnerConfigurationEN7xgboost9LearnerIOEN7xgboost11LearnerImplEUnknown linear updater /__w/ml-builds/ml-builds/xgboost/src/linear/linear_updater.ccUpdateFeaturetop_kCoordinateParamunknown coordinate selector: CoordinateUpdatercoordinate_paramThe number of top features to select in 'thrifty' feature_selector. The value of zero means using all the features./__w/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.hUpdate linear model according to coordinate descent algorithm.nnomnN7xgboost13LinearUpdaterEN7xgboost6linear15FeatureSelectorEN7xgboost6linear21CyclicFeatureSelectorEN7xgboost6linear22ShuffleFeatureSelectorEN7xgboost6linear21RandomFeatureSelectorEN7xgboost6linear21GreedyFeatureSelectorEN7xgboost6linear22ThriftyFeatureSelectorEN7xgboost6linear17CoordinateUpdaterE*N7xgboost6linearUlvE_E/__w/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. @xN7xgboost6linear14ShotgunUpdaterE*N7xgboost6linearUlvE_EWARNING: DEBUG: INFO: info.group_ptr_.size() >= 2least 2 pairs of samples.n_classes != 0Check failed: !labels.empty()auc <= 1Total AUC across groups: , valid groups: auc <= 1.0f/__w/ml-builds/ml-builds/xgboost/src/metric/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/metric/auc.cc/__w/ml-builds/ml-builds/xgboost/src/metric/auc.hInvalid group with less than 3 samples is found on worker . Calculating AUC value requires at labels.size() == predts.size()info.weights_.Size() == info.group_ptr_.size() - 1info.group_ptr_.back() == info.labels_.Size()Dataset contains only positive or negative samples.Receiver Operating Characteristic Area Under the Curve.N7xgboost6MetricEN7xgboost6metric7EvalAUCE*N7xgboost6metricUlPKcE_E?gamma-nloglikgamma-deviancepoisson-nloglikmphemapemaermslermsetweedie-nloglik@%fRooted mean square error.Rooted mean square log error.Mean absolute error.Mean Pseudo Huber error.Binary classification error.tweedie-nloglik/__w/ml-builds/ml-builds/xgboost/src/metric/elementwise_metric.cuCheck failed: param != nullptrtweedie-nloglik must be in format tweedie-nloglik@rhoCheck failed: rho_ < 2 && rho_ >= 1tweedie variance power must be in interval [1, 2)sscanf(param, "%f", &threshold_) == 1unable to parse the threshold value for the error metricpreds.Size() == info.labels_.Size()label and prediction size not match, hint: use merror or mlogloss for multi-class classificationMean absolute percentage error.Negative loglikelihood for logistic regression.Negative loglikelihood for poisson regression.Residual deviance for gamma regression.Negative log-likelihood for gamma regression.tweedie-nloglik@rho for tweedie regression.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_E$]@$tI$tUnknown metric function /__w/ml-builds/ml-builds/xgboost/src/metric/metric.ccCannot find a GPU metric builder for metric . Resorting to the CPU builderpreds.Size() == 0nclass >= 1U num_class= but found in label/__w/ml-builds/ml-builds/xgboost/src/metric/multiclass_metric.cuCheck failed: preds.Size() % info.labels_.Size() == 0label and prediction size not matchmlogloss and merror are only used for multi-class classification, use logloss for binary classificationCheck failed: label_error >= 0 && label_error < static_cast(n_class)MultiClassEvaluation: label must be in [0, num_class),Multiclass classification error.Multiclass negative loglikelihood.N7xgboost6metric14EvalMClassBaseINS0_14EvalMatchErrorEEEN7xgboost6metric14EvalMatchErrorEN7xgboost6metric14EvalMClassBaseINS0_16EvalMultiLogLossEEEN7xgboost6metric16EvalMultiLogLossE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E]Bcox-nloglikaucpr%u[-]?preAMS must be in format ams@kams@gptr.size() != 0Ugptr.back() == preds.Size()info.labels_.Size() != 0Ulabel set cannot be emptydat[1] > 0.0fdat[0] <= dat[1]AUC-PR: AUC > 1.0AMS metric for higgs.precision@k for rank.ndcg@k for rank.map@k for rank.Check failed: !distributedbest-ams-ratio=Check failed: !auc_errorAUC-PR: error in calculation/__w/ml-builds/ml-builds/xgboost/src/metric/rank_metric.cclabel size predict size not matchmust specify group when constructing rank fileEvalRank: group structure must match number of predictiongptr.back() == info.labels_.Size()EvalAucPR: group structure must match number of predictionAUC-PR: the dataset only contains pos or neg samplesArea under PR curve for both classification and rank.Negative log partial likelihood of Cox proportional hazards model.Cox metric does not support distributed evaluationmetric AMS do not support distributed evaluation;wwwTwlwx(N7xgboost6metric14EvalRankConfigEN7xgboost6metric7EvalAMSEN7xgboost6metric8EvalRankEN7xgboost6metric13EvalPrecisionEN7xgboost6metric8EvalNDCGEN7xgboost6metric7EvalMAPEN7xgboost6metric7EvalCoxEN7xgboost6metric9EvalAucPRE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E*N7xgboost6metricUlPKcE1_E*N7xgboost6metricUlPKcE2_E*N7xgboost6metricUlPKcE3_E*N7xgboost6metricUlPKcE4_E@$@aft-nloglikinterval-regression-accuracyCheck failed: metric_/__w/ml-builds/ml-builds/xgboost/src/metric/survival_metric.cuAFT 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 distributionNegative log likelihood of Accelerated Failure Time model.N7xgboost6metric20AFTNLogLikDispatcherEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common18NormalDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common20LogisticDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common19ExtremeDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_30EvalIntervalRegressionAccuracyEEE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E-q=' @;f?info.weights_.Size() == ndataUnrecognized distributionAFT loss functionsurvival:aft/__w/ml-builds/ml-builds/xgboost/src/objective/../common/transform.hNot part of device code. WITH_CUDA: /__w/ml-builds/ml-builds/xgboost/src/objective/aft_obj.cuinfo.labels_lower_bound_.Size() == ndatainfo.labels_upper_bound_.Size() == ndataNumber of weights should be equal to number of data points.N7xgboost11ObjFunctionEN7xgboost3obj6AFTObjE*N7xgboost3objUlvE_E..@ؗҜ<@@ppApreds.size=, label.size=binary:hinge/__w/ml-builds/ml-builds/xgboost/src/objective/hinge.culabels are not correctly providedHinge loss. Expects labels to be in [0,1f]N7xgboost3obj8HingeObjE*N7xgboost3objUlvE_ESoftmaxMultiClassParamlabel.Size() * num_class: preds.Size(): softmax_multiclass_paramNumber of output class in the multi-class classification./__w/ml-builds/ml-builds/xgboost/src/objective/multiclass_obj.cuCheck failed: preds.Size() == (static_cast(param_.num_class) * info.labels_.Size())SoftmaxMultiClassObj: label size and pred size does not match. SoftmaxMultiClassObj: label must be in [0, num_class).Softmax for multi-class classification, output class index.Softmax for multi-class classification, output probability distribution.N7xgboost3obj20SoftmaxMultiClassObjE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_EҜ 0.0f && base_score < 1.0fbase_score must be in (0,1) for logistic loss, got: Scale the weight of positive examples by this factorMaximum delta step we allow each weight estimation to be. This parameter is required for possion regression.Tweedie variance power. Must be between in range [1, 2).PoissonRegression: label must be nonnegativeGammaRegression: label must be positive.TweedieRegression: label must be nonnegativeRegression 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.Poisson regression for count data.Cox regression for censored survival data (negative labels are considered censored).Gamma regression for severity data.Tweedie regression for insurance data.Check failed: last_abs_y <= abs_yCoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed!label must be in [0,1] for logistic regressionlabel must be greater than -1 for rmsle so that log(label + 1) can be valid.N7xgboost3obj10RegLossObjINS0_16LinearSquareLossEEEN7xgboost3obj10RegLossObjINS0_15SquaredLogErrorEEEN7xgboost3obj10RegLossObjINS0_18LogisticRegressionEEEN7xgboost3obj10RegLossObjINS0_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????/__w/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 != 0Ignoring 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. /__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/any.hm->NumColumns() == model.learner_model_param->num_featureNumber of columns in data must equal to trained model.out_preds->size() == p_fmat->Info().num_row_ * model.learner_model_param->num_output_groupout_preds->Size() == n * base_score = ncolumns != 0Make predictions using CPU.0HHHGGGGxGXGB@HMMMMMZN.NFNMINN7xgboost9predictor12CPUPredictorESt10shared_ptrIN7xgboost4data12DenseAdapterEESt10shared_ptrIN7xgboost4data10CSRAdapterEE*N7xgboost9predictorUlPKNS_16GenericParameterEE_E?Unknown predictor type _Map_base::at[Internal error]: DMatrix: has expired./__w/ml-builds/ml-builds/xgboost/src/predictor/predictor.ccCheck failed: container_.find(m) != container_.cend()Check failed: container_.at(m).ref.lock()N7xgboost9PredictorEnewsize != 0With error: /__w/ml-builds/ml-builds/xgboost/src/tree/constraints.ccFailed to parse feature interaction constraint: _std::floor(d) == d/__w/ml-builds/ml-builds/xgboost/src/tree/param.ccFound floating point number in interaction constraintsUnknown value type for interaction constraint:/__w/ml-builds/ml-builds/xgboost/src/tree/tree_model.ccparam.num_nodes == static_cast(nodes_.size())param.num_nodes == static_cast(stats_.size())param.deprecated_num_roots == 1/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././json.h, Expect '"' but reach end of line , JSON object expect '}' or ',' ' in feature map is categorical but tree node is numerical. in feature map is numerical but tree node is categorical.this->split_types_.size() == param.num_nodesthis->GetSplitCategoriesPtr().size() == param.num_nodesstd::numeric_limits::min() != max_cat/__w/ml-builds/ml-builds/xgboost/include/xgboost/tree_model.hparam.num_nodes < std::numeric_limits::max()number of nodes in the tree exceed 2^31fi->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_deletedNumber of features used in tree construction.Size of leaf vector, reserved for vector treeEdge color when meets the node condition.Edge color when doesn't meet the node condition.Passed to graphiz via graph_attr.Conditional node configurationAny other extra attributes for graphviz `graph_attr`.Minimum loss reduction required to make a further partition.Maximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policyMaximum number of leaves; 0 indicates no limit.if using histogram-based algorithm, maximum number of bins per featureTree growing policy. 0: favor splitting at nodes closest to the node, i.e. grow depth-wise. 1: favor splitting at nodes with highest loss change. (cf. LightGBM)Minimum sum of instance weight(hessian) needed in a child.L2 regularization on leaf weightL1 regularization on leaf weightDefault 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 constraintRow subsample ratio of training instance.Sampling method. 0: select random training instances uniformly. 1: select random training instances with higher probability when the gradient and hessian are larger. (cf. CatBoost)Subsample ratio of columns, resample on each node (split).Subsample ratio of columns, resample on each level.Subsample ratio of columns, resample on each tree construction.EXP Param: Sketch accuracy of approximate algorithm.EXP Param: Sketch accuracy related parameter of approximate algorithm.EXP Param: Cache aware optimization.Whether the refresh updater needs to update leaf values.Constraint of variable monotonicityConstraints for interaction representing permitted interactions.The constraints must be specified in the form of a nest list,e.g. [[0, 1], [2, 3, 4]], where each inner list is a group ofindices of features that are allowed to interact with each other.See tutorial for more informationThe criteria to use for ranking splitspercentage threshold for treating a feature as sparsewhen 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.when grouping features, how much effort to expend to prevent singleton groups. We'll try to insert each feature into existing groups before creating a new group for that feature; to save time, only up to (max_search_group) of existing groups will be considered. If set to zero, ALL existing groups will be examined.loss_changes.size() == n_nodesbase_weights.size() == n_nodesdefault_left.size() == n_nodesn_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) {nid} [ label="leaf={leaf-value}" {params}] digraph { graph [ rankdir={rankdir} ] {graph_attrs} {nodes}}{nid}:[{fname}] yes={yes},no={no} {nid} -> {child} [label="{branch}" color="{color}"] {nid} [ label="{fname}:{cond}" {params}] {nid} [ label="{fname}{<}{cond}" {params}] {tabs}{nid}:leaf={leaf}{stats}{{properties} {stat}, "children": [{left}, {right} {indent}]}{ "nodeid": {nid}, "leaf": {leaf} {stat}} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "yes": {yes}, "no": {no} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {left}, "no": {right}, "missing": {missing} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {right}, "no": {left}, "missing": {missing}{tabs}{nid}:[{fname}<{cond}] yes={left},no={right},missing={missing}{tabs}{nid}:[f{fname}<{cond}] yes={left},no={right},missing={missing}{tabs}{nid}:[{fname}:{cond}] yes={right},no={left},missing={missing}, "gain": {loss_chg}, "cover": {sum_hess},gain={loss_chg},cover={sum_hess}Dump text representation of treeDump json representation of treeDump graphviz representation of tree graph [ {key}="{value}" ] The following parameters for graphviz are not recognized: Failed to parse graphviz parameters: Line , around ^`basic_string::replaceUnknown Model Builder:{param.num_nodes != 0ch == '\"'Error at, Expect '"' but get 'unknown string escape \ch == ','ch == ':', Expect ':' but get 'ch == '{', Expect '{' but get 'mean_values->size() > 0UCheck failed: is_numericalCheck failed: is_categoricalUnknown feature map type.pos != std::string::nposcategories_segmentscategories_sizescategories_nodescategoriesj_end - j_begin != 0unique_path[i].pweight == 0Unique path must have zero weightCheck failed: node.IsLeaf()num_nodesnum_deletedTreeParamdouble#0000FFyes_color#FF0000no_colorrankdircondition_node_paramsLeaf node configurationleaf_node_paramsgraph_attrsGraphvizParammin_split_lossmax_depthmax_leavesmax_binlossguidedepthwisegrow_policymin_child_weightreg_lambdareg_alpharightlearndefault_directionsubsamplegradient_basedsampling_methodcolsample_bynodecolsample_bylevelcolsample_bytreesketch_epssketch_ratiocache_optrefresh_leafmonotone_constraintsinteraction_constraintselastic_net,monotonicsplit_evaluatorsparse_thresholdmax_conflict_ratemax_search_grouptree_paramn_nodes != 0loss_changessum_hessiansum_hessian.size() == n_nodesbase_weightsleft_childrenlefts.size() == n_nodesright_childrenrights.size() == n_nodesparentsparents.size() == n_nodessplit_indicesindices.size() == n_nodessplit_conditionsconds.size() == n_nodesdefault_leftsplit_type{newline}{indent}{nodes}{newline}{indent}{nid}{leaf-value}{params}{parent} {left} {right}{parent}{left}{rankdir}{graph_attrs}{fname}{yes}{no}{parent}{stat} {left} {right}{stat}, missingyesno{child}{color}{branch}%u{cond}<{<}{nodes} ,cover={cover}{tabs}{leaf}{stats}{properties}, "cover": {sum_hess} {sum_hess}{depth}{missing}{loss_chg}dot" edge{key}{value}0L0/L00N7xgboost7RegTreeEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryISt6vectorIiSaIiEEEES5_EEN4dmlc9parameter10FieldEntryISt6vectorIiSaIiEEEEN7xgboost13TreeGeneratorEN7xgboost13TextGeneratorEN7xgboost13JsonGeneratorEN7xgboost17GraphvizGeneratorE*N7xgboostUlRKNS_10FeatureMapERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE_E*N7xgboostUlRKNS_10FeatureMapERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE0_E*N7xgboostUlRKNS_10FeatureMapENSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE1_E?HgY?@חA?Unknown tree updater /__w/ml-builds/ml-builds/xgboost/src/tree/tree_updater.ccgrow_colmakerthis->max_depth <= 31ridx < position_.size()ridx exceed bound ridx= pos=opt_dense_colColMakerTrainParamcolmaker_train_param/__w/ml-builds/ml-builds/xgboost/src/tree/updater_colmaker.ccCheck failed: param_.cache_optSupport for `cache_opt' is removed in 1.0.0/__w/ml-builds/ml-builds/xgboost/src/tree/param.hMax leaves and max depth cannot both be unconstrained.max_depth can not be greater than 31 as that might generate 2 ** 32 - 1 nodes.EXP Param: speed optimization for dense column.fmat.Info().num_row_ == position_.size()param_.sampling_method == TrainParam::kUniformOnly uniform sampling is supported, gradient-based sampling is only support by GPU Hist./__w/ml-builds/ml-builds/xgboost/src/tree/../common/transform.hUpdater `grow_colmaker` or `exact` tree method doesn't support distributed training.Updater `grow_colmaker` or `exact` tree method doesn't support external memory training.Grow tree with parallelization over columns.N7xgboost11TreeUpdaterEN7xgboost4tree8ColMaker7BuilderEN7xgboost4tree8ColMakerE*N7xgboost4treeUlvE_Egrow_histmakergrow_local_histmakerfv=, hist.size=hist[]=, hist.last=sketch->temp.size < max_size, stemp.sizeINFO: rmax=, sum_total=, naxt_goal=, size=ret > 0Ufid * 2 + 1 < fminmax_.size()fid * 2 < fminmax_.size()istart != hist.size check quantile stats, nbig=, n= srcsize=, maxsize=, range=, chunk=] rmin=, rmax=, wmin=, v=Check failed: nbig < nsketch->temp.size <= max_size, stemp.size=offset == -2this->qexpand_.size() == 1U/__w/ml-builds/ml-builds/xgboost/src/tree/updater_histmaker.ccnode2workindex_[nid] == static_cast(wid)/__w/ml-builds/ml-builds/xgboost/src/tree/./updater_basemaker-inl.hinvalid maximum size max_size=/__w/ml-builds/ml-builds/xgboost/src/tree/./param.hFeatHelper fid exceed query bound Check failed: param_.max_depth > 0max_depth must be larger than 0Check failed: tree[nid].IsLeaf()/__w/ml-builds/ml-builds/xgboost/src/tree/../common/quantile.hquantile: 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)Finalize: invalid maximum size, max_size=summary_array_.size() == sketchs_.size()this->wspace_.rptr.size() == (fset.size() + 1) * this->qexpand_.size() + 1this->wspace_.rptr.back() == this->wspace_.cut.size()Tree constructor that uses approximate histogram construction.Tree constructor that uses approximate global of histogram construction.l̨N7xgboost4tree9BaseMakerEN7xgboost4tree9HistMakerEN7xgboost4tree11CQHistMakerEN7xgboost4tree23GlobalProposalHistMakerEZN7xgboost4tree11CQHistMaker10CreateHistERKSt6vectorINS_6detail20GradientPairInternalIfEESaIS5_EEPNS_7DMatrixERKS2_IjSaIjEERKNS_7RegTreeEEUlvE_*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_Eư>o;o:nid >= 1tree pruning end, extra nodes, pruned nodes, max_depth=/__w/ml-builds/ml-builds/xgboost/src/tree/updater_prune.ccCheck failed: !tree[pid].IsLeaf()Pruner that prune the tree according to statistics.N7xgboost4tree10TreePrunerE*N7xgboost4treeUlvE_Ebegin < endi < ranges_.size()i < first_dimension_.size()exponent <= modUpdatePredictionCacheout_preds.Size() > 0Umax_bin_per_feat >= 2vector::_M_fill_insertQuantile::BuilderQuantileHistMakerGmatInitializationInitDataInitSamplingmin_nbins_per_feature > 0UCPUHistMakerTrainParamsingle_precision_histogramid != kMaxcpu_hist_train_paramSplitSiblingsend > beginnid < nodes_n_left + n_right == e.Size()begin + n_left <= e.endany_missing == any_missing_any_missing == truerow_ptr_[nid] == kMaxApplySplittid < nthreads_EvaluateSplitsExpandTreeUpdategrow_fast_histmaker/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/../../common/threading_utils.h/__w/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.ccCheck failed: (*p_last_tree_)[nid].IsLeaf()/__w/ml-builds/ml-builds/xgboost/src/tree/./updater_quantile_hist.hout_preds.DeviceIdx() == GenericParameter::kCpuId/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/../../common/row_set.helem_of_each_node_.size() == 0U/__w/ml-builds/ml-builds/xgboost/src/tree/./../common/../common/column_matrix.h/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/histogram.hgmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_valgmat_bin_size == kUint32BinsTypeSizebins_type_size_ == kUint32BinsTypeSizegrow_fast_histmaker is deprecated, use grow_quantile_histmaker instead.Check failed: (param_.max_depth > 0 || param_.max_leaves > 0)max_depth or max_leaves cannot be both 0 (unlimited); at least one should be a positive quantity.max_depth cannot be 0 (unlimited) when grow_policy is depthwise.row_indices.size() == info.num_row_upper_bound < static_cast(std::numeric_limits::max())Use single precision to build histograms./__w/ml-builds/ml-builds/xgboost/src/tree/./hist/../../common/hist_util.h/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/evaluate_splits.hCheck failed: !features.empty()Attempted to load internal configuration for a model file that was generated by a previous version of XGBoost. A likely cause for this warning is that the model was saved with saveRDS() in R or pickle.dump() in Python. We strongly ADVISE AGAINST using saveRDS() or pickle.dump() so that the model remains accessible in current and upcoming XGBoost releases. Please use xgb.save() instead to preserve models for the long term. For more details and explanation, see https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.htmlnodes_for_subtraction_trick_.size() == nodes_for_explicit_hist_build_.size()cut_ptr[fidx] <= static_cast(std::numeric_limits::max())cut_ptr[fidx + 1] <= static_cast(std::numeric_limits::max())Check failed: e.begin != nullptrbegin + n_left + n_right == e.end(*p_tree)[nid].LeftChild() + 1 == (*p_tree)[nid].RightChild()sizeof(BinIdxType) == bins_type_size_/__w/ml-builds/ml-builds/xgboost/src/tree/./../common/partition_builder.h/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/../../common/transform.haccess element that is not in the setnodes == targeted_hists.size()(Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram.Grow tree using quantized histogram.FbRKN7xgboost4tree14CPUExpandEntryES3_EN7xgboost4tree17QuantileHistMakerEN7xgboost4tree17QuantileHistMaker7BuilderIfEEN7xgboost4tree17QuantileHistMaker7BuilderIdEE*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_EN7xgboost6common6ColumnIhEEN7xgboost6common11DenseColumnIhLb1EEEN7xgboost6common12SparseColumnIhEEN7xgboost6common6ColumnItEEN7xgboost6common11DenseColumnItLb1EEEN7xgboost6common12SparseColumnItEEN7xgboost6common6ColumnIjEEN7xgboost6common11DenseColumnIjLb1EEEN7xgboost6common12SparseColumnIjEEN7xgboost6common11DenseColumnIhLb0EEEN7xgboost6common11DenseColumnItLb0EEEN7xgboost6common11DenseColumnIjLb0EEEPFbRKN7xgboost4tree14CPUExpandEntryES3_ESt23_Sp_counted_ptr_inplaceIN7xgboost6common13ColumnSamplerESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost6common16PartitionBuilderILm2048EE9BlockInfoELN9__gnu_cxx12_Lock_policyE2EE::max()Refresher that refreshes the weight and statistics according to data.N7xgboost4tree13TreeRefresherEZN7xgboost4tree13TreeRefresher6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKSt6vectorIPNS_7RegTreeESaISC_EEEUlvE0_*N7xgboost4treeUlvE_EsyncSyncher that synchronize the tree in all distributed nodes.N7xgboost4tree11TreeSyncherE*N7xgboost4treeUlvE_Erabit_tracker_urirabit_tracker_portrabit_task_idDMLC_TRACKER_URIDMLC_TRACKER_PORTDMLC_TASK_IDDMLC_ROLErabit_world_sizerabit_hadoop_moderabit_tree_reduce_minsizerabit_reduce_ring_mincountrabit_reduce_buffer%lu%cinvalid format for %sDMLC_WORKER_CONNECT_RETRYrabit_bootstrap_cacherabit_debugrabit_timeoutrabit_timeout_secrabit_enable_tcp_no_delayCreateSocket %s Error:%scannot obtain address of %sDoes not support IPv6Connect to (failed): [] ConnectSendAllReConnectLink failure 1RecvAllReConnectLink failure 2ReConnectLink failure 3error during send SendStrFailed to shutdown due toworker256MBDMLC_NUM_ATTEMPTPoll timeoutPollAllreduce: boundary checkbuffer size inconsistentmust assign buffer_sizeAllreduce: size checkAllreduce: boundary errorneed to assume rank structureAllgatherRing failedwrite ptr boundary check[%d] read_ptr boundary checkAllreduce failedBroadcast failedtask connected to the trackerReConnectLink failure 4 got new rank 0.0.0.0TryBindHostGetSockErrorReConnectLink failure 5ReConnectLink failure 6ReConnectLink failure 7ReConnectLink failure 8error during send RecvStrReConnectLink failure 9ReConnectLink failure 10ReConnectLink failure 12ReConnectLink failure 13ReConnectLink failure 14AcceptReConnectLink failure 15ReConnectLink: bad socketSetNonBlock-1SetNonBlock-2SetKeepAlivefailed in ReconnectLink mapred_tip_id%[^=]=%smapreduce_task_idmapred_task_idmapred_map_tasksmapreduce_job_mapscan only call Init oncefail to get host namestartrabit_num_trialrabit_reduce_ring_mincount should be greater than 0invalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB}rabit_timeout_sec should be non negative secondRetry connect to ip(retry time sync::Invalid tracker message, init failureSocket::Close double close the socket or close without create/__w/ml-builds/ml-builds/xgboost/rabit/src/allreduce_base.cctoo large type_nbytes=%lu, buffer_size=%lu/__w/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/socket.hReadToRingBuffer: max_size_read checkReadToRingBuffer: buffer not allocatedBroadcast: root should be smaller than world sizemust keep rank to same if the node already have onetracker got overwhelmed and not able to assign correct rankReConnectLink fail to bind the ports specifiedReConnectLink failure, link rank inconsistentOverride a link that is activecannot find parent in the linkcannot find prev ring in the linkcannot find next ring in the linkhadoop_mode is set but cannot find mapred_task_idhadoop_mode is set but cannot find mapred_map_tasksRabit Module currently only work with dmlc workerN5rabit6engine7IEngineEN5rabit6engine13AllreduceBaseEFailed to shutdown RABIT worker.DataType does not support bitwise or operationFailed to initialize RABIT.unknown data_typeunknown enum_opnot implementedRead pickle string]x]H]]\\ X X8YYXXxXHXXhYZhZ8ZZYYxYZ[[[h[8[[Z(\`_`_^^(_(_^(_N5rabit5c_api11ReadWrapperEN5rabit5c_api12WriteWrapperEthe rabit has not been initializedcannot initialize reduce handle twicemust initialize handle to call AllReducecannot call ParseNextNo threadsign == true.split.partname_cache.size() == 1UInvalid uri argument format for key in arg for value in arg name_args.size() == 1UUnknown data type File formatindexing_modeLibSVMParserParamlibfmLibFMParserParamFile format.label_columndelimiterweight_columnCSVParserParamoffset.back() == index.size()param_.format == "csv"param_.format == "libfm"param_.format == "libsvm"Bad RowBlock formatCheck failed: fi->Read(&qid)MB read,finish reading at finish reading at %g MB/secCheck failed: TryLoadCache()failed to build cache file qid:Delimiter '' is not found in the line. Expected 'chunk.size != 0U/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/threadediter.hCheck failed: out_data_ != NULLCalling Value at beginning or end?/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././parameter.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./././strtonum.hCheck failed: base <= 10 && base >= 2/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/uri_spec.honly one `#` is allowed in file path for cachefile specificationCheck failed: std::getline(is, kv.first, '=')Check failed: std::getline(is, kv.second)/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data.ccIf >0, treat all feature indices as 1-based. If =0, treat all feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.If >0, treat all field and feature indices as 1-based. If =0, treat all field and feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.Column index (0-based) that will put into label.Delimiter used in the csv file.Column index that will put into instance weights./__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./row_block.hlabel.size() + 1 == offset.size()Check failed: offset.back() == value.size() || value.size() == 0/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/csv_parser.hCheck failed: param_.label_column != param_.weight_column || param_.label_column < 0Must have distinct columns for labels and instance weights/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/libfm_parser.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.hCheck failed: fi->Read(&label)Check failed: fi->Read(&weight)Check failed: fi->Read(&field)Check failed: fi->Read(&index)Check failed: fi->Read(&value)Check failed: fi->Read(&max_field, sizeof(IndexType))Check failed: fi->Read(&max_index, sizeof(IndexType))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) != kDestroyCheck failed: !producer_sig_processed_.load(std::memory_order_acquire)Check failed: producer_sig_.load(std::memory_order_acquire) == kProduceMake sure you call BeforeFirst not inconcurrent with Next!Check failed: produce_end_.load(std::memory_order_acquire)/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/disk_row_iter.hCheck failed: out->field.size() == out->index.size()Check failed: out->label.size() + 1 == out->offset.size()' as the delimiter to separate fields.Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size()/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/././text_parser.hNSt6thread5_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_policyE2EEN4dmlc12ScopedThreadEN4dmlc8DataIterINS_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_ZN4dmlc4da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compile with DMLC_USE_HDFS=1 to use hdfsPlease compile with DMLC_USE_S3=1 to use S3/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io.ccPlease compile with DMLC_USE_AZURE=1 to use Azure/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/single_file_split.hInputSplit do not support writeCheck failed: part_index == 0 && num_parts == 1/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/cached_input_split.hResetPartition is not supported in CachedInputSplitCheck failed: nread == sizeof(size) has invalid cache file formatCheck failed: fi_->Read(p->begin, size) == sizeSingleFileSplit: fail to open invalid input parameter for InputSplit::Createneed to pass index file to use IndexedRecordIOCheck failed: this->InitCachedIter()Failed to initialize CachedIterviewfs://s3://http://https://azure://unknown filesystem protocol hdfs://BeforeFirst is not supportedstdinCheck failed: fp_ != NULLCheck failed: part < nsplitindexed_recordiounknown input split type rbFvvEN4dmlc10InputSplitEN4dmlc2io15SingleFileSplitEN4dmlc8DataIterINS_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_policyE2EECheck failed: begin != end/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.ccN4dmlc2io12LineSplitterEinvalid record io formatCheck failed: p >= pbegin + 2Invalid RecordIO FormatCheck failed: cflag == 1U/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/recordio_split.ccCheck failed: fi->Read(&lrec, sizeof(lrec)) != 0(reinterpret_cast(begin) & 3UL) == 0U(reinterpret_cast(end) & 3UL) == 0UCheck failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->end(reinterpret_cast(chunk->begin) & 3UL) == 0U(reinterpret_cast(chunk->end) & 3UL) == 0UCheck failed: chunk->begin <= chunk->endCheck failed: p[0] == RecordIOWriter::kMagicN4dmlc2io16RecordIOSplitterEexpanded_list.size() == 1ul/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.ccIndexedRecordIOSplitter does not support multiple index filesN4dmlc2io23IndexedRecordIOSplitterE/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/input_split_base.ccCheck failed: offset_end_ >file_offset_[file_ptr_end_]Check failed: file_ptr_end_ < files_.size()file offset not calculated correctlyThis could due to compiler version, g++-4.9 is neededCannot find any files that matches the URI pattern Check failed: files_[i].size % align_bytes == 0curr=,begin=,end=,fileptr=,fileoffset=offset[^$\.*+?()[]{}|.[\*^$.[\()*+?{|^$.[\*^$ .[\()*+?{|^$ bad regex files_.size() != 0Ufile do not align by bytesNULSOHSTXETXEOTENQACKalertbackspacenewlinevertical-tabform-feedcarriage-returnSOSIDLEDC1DC2DC3DC4NAKSYNETBCANEMSUBESCIS4IS3IS2IS1exclamation-markquotation-marknumber-signdollar-signpercent-signampersandapostropheleft-parenthesisright-parenthesisasteriskplus-signcommahyphenperiodonetwothreefourfivesixsevenninesemicolonless-than-signequals-signgreater-than-signquestion-markcommercial-atAGJPRSVWleft-square-bracketbackslashright-square-bracketcircumflexunderscoregrave-accentjzleft-curly-bracketvertical-lineright-curly-brackettildeDELalnumblankcntrlgraphlowerprintpunctupperxdigitPHh@PN4dmlc2io14InputSplitBaseESt23_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 error: LocalFileSystem.GetPathInfo: stdoutwbCheck failed: allow_null LocalFileSystem::Open "": FileStream.Write incomplete../__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/local_filesys.ccLocalFileSystem.GetPathInfo: detected symlink Check failed: !std::fseek(fp_, static_cast(pos), SEEK_SET)Check failed: std::fwrite(ptr, 1, size, fp_) == sizeLocalFileSystem.ListDirectory N4dmlc2io15LocalFileSystemEN4dmlc2io10FileStreamElstat(path.c_str(), &sb) == 0Couldn't remove file ~TemporaryDirectory(): /__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/filesystem.hdmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/filesys.ccCheck failed: !IsSymlink(info.path.name)Symlink not supported in TemporaryDirectorySuccessfully deleted temporary directory Could not remove temporary directory N4dmlc2io10FileSystemE;ȝܟ8VHgr@v̠ 8 KJKb8N8@x 4^ ^ܢ`Z]H(HX1H(Vxer(vpxHHаxH(XPX Ȱ!Kx NPOXpض`HЙx8`ع(ؼxHؿ(88`xHX` 8x 8/H`NHpX`(X0`H6^^aXȬ`(8h 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