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4dmlc6ParserImfEE_ZTSN4dmlc6ParserIjiEE_ZTIN4dmlc6ParserIjiEE_ZTSN4dmlc6ParserImiEE_ZTIN4dmlc6ParserImiEE_ZTSN4dmlc6ParserIjlEE_ZTIN4dmlc6ParserIjlEE_ZTSN4dmlc6ParserImlEE_ZTIN4dmlc6ParserImlEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEE_ZTSN4dmlc4data11DiskRowIterIjfEE_ZTIN4dmlc4data11DiskRowIterIjfEE_ZTSN4dmlc4data12BasicRowIterIjfEE_ZTIN4dmlc4data12BasicRowIterIjfEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEE_ZTSN4dmlc4data11DiskRowIterImfEE_ZTIN4dmlc4data11DiskRowIterImfEE_ZTSN4dmlc4data12BasicRowIterImfEE_ZTIN4dmlc4data12BasicRowIterImfEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEE_ZTSN4dmlc4data11DiskRowIterIjiEE_ZTIN4dmlc4data11DiskRowIterIjiEE_ZTSN4dmlc4data12BasicRowIterIjiEE_ZTIN4dmlc4data12BasicRowIterIjiEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEE_ZTSN4dmlc4data11DiskRowIterImiEE_ZTIN4dmlc4data11DiskRowIterImiEE_ZTSN4dmlc4data12BasicRowIterImiEE_ZTIN4dmlc4data12BasicRowIterImiEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEE_ZTSN4dmlc4data11DiskRowIterIjlEE_ZTIN4dmlc4data11DiskRowIterIjlEE_ZTSN4dmlc4data12BasicRowIterIjlEE_ZTIN4dmlc4data12BasicRowIterIjlEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEE_ZTSN4dmlc4data11DiskRowIterImlEE_ZTIN4dmlc4data11DiskRowIterImlEE_ZTSN4dmlc4data12BasicRowIterImlEE_ZTIN4dmlc4data12BasicRowIterImlEE_ZTSN4dmlc4data10ParserImplIjfEE_ZTIN4dmlc4data10ParserImplIjfEE_ZTSN4dmlc4data14TextParserBaseIjfEE_ZTIN4dmlc4data14TextParserBaseIjfEE_ZTSN4dmlc4data12LibSVMParserIjfEE_ZTIN4dmlc4data12LibSVMParserIjfEE_ZTSN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTIN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTSN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTIN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTSN4dmlc4data14ThreadedParserIjfEE_ZTIN4dmlc4data14ThreadedParserIjfEE_ZTSN4dmlc4data10ParserImplImfEE_ZTIN4dmlc4data10ParserImplImfEE_ZTSN4dmlc4data14TextParserBaseImfEE_ZTIN4dmlc4data14TextParserBaseImfEE_ZTSN4dmlc4data12LibSVMParserImfEE_ZTIN4dmlc4data12LibSVMParserImfEE_ZTSN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTIN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTSN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTIN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTSN4dmlc4data14ThreadedParserImfEE_ZTIN4dmlc4data14ThreadedParserImfEE_ZTSN4dmlc4data11LibFMParserIjfEE_ZTIN4dmlc4data11LibFMParserIjfEE_ZTSN4dmlc4data11LibFMParserImfEE_ZTIN4dmlc4data11LibFMParserImfEE_ZTSN4dmlc4data9CSVParserIjfEE_ZTIN4dmlc4data9CSVParserIjfEE_ZTSN4dmlc4data9CSVParserImfEE_ZTIN4dmlc4data9CSVParserImfEE_ZTSN4dmlc4data10ParserImplIjiEE_ZTIN4dmlc4data10ParserImplIjiEE_ZTSN4dmlc4data14TextParserBaseIjiEE_ZTIN4dmlc4data14TextParserBaseIjiEE_ZTSN4dmlc4data9CSVParserIjiEE_ZTIN4dmlc4data9CSVParserIjiEE_ZTSN4dmlc4data10ParserImplImiEE_ZTIN4dmlc4data10ParserImplImiEE_ZTSN4dmlc4data14TextParserBaseImiEE_ZTIN4dmlc4data14TextParserBaseImiEE_ZTSN4dmlc4data9CSVParserImiEE_ZTIN4dmlc4data9CSVParserImiEE_ZTSN4dmlc4data10ParserImplIjlEE_ZTIN4dmlc4data10ParserImplIjlEE_ZTSN4dmlc4data14TextParserBaseIjlEE_ZTIN4dmlc4data14TextParserBaseIjlEE_ZTSN4dmlc4data9CSVParserIjlEE_ZTIN4dmlc4data9CSVParserIjlEE_ZTSN4dmlc4data10ParserImplImlEE_ZTIN4dmlc4data10ParserImplImlEE_ZTSN4dmlc4data14TextParserBaseImlEE_ZTIN4dmlc4data14TextParserBaseImlEE_ZTSN4dmlc4data9CSVParserImlEE_ZTIN4dmlc4data9CSVParserImlEE_ZTSZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlPPSt6vectorINS0_17RowBlockContainerIjfEESaIS8_EEE__ZTSZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlvE0__ZTSZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlPPSt6vectorINS0_17RowBlockContainerImfEESaIS8_EEE__ZTSZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlvE0__ZTSZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjfEEE__ZTSZN4dmlc4dat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MLl$XII4EMD]0H}PLm(C*L$H}@L$LLt M[Ll$XIPIAMPLmHB/H$`M'LL$DMHt$GDM}LHt$H$1$vLD$XH$HL$LL1uLl$XH$|Ht$H$1vL\$XH$HL$LHuLd$XL$Ht$H$1vLT$XH$HL$ LL葭uLt$XH$AL$H$HHLHL$8vxMULMEL|$0zDMfHt$L$1HLL$8L$vLT$XHEHLULLѬuLl$XL}Ht$H} 1vHL$XHE HHM0LL蕬uLl$XHU 1Ht$H}@1@vHt$XHE@HHuPLLUuLl$XH}@DL$H$LH|$8'vFfDM/HL$0DM0fMMHt$L$1HLD$8L$vHt$XHEHHuLL虫uLl$XHMHt$H}@1HvL|$XHE@HL}PLL]uLl$XH}@Ht$H} 1vHT$XHE HHU0LLuLl$XLU L$H$L9+f.I`L9t$@H9tMT$PIrVvI|$ M\$0L9tIT$0HrVvI<$Il$H9tIt$HVvH$VvL$IEIfInfHnHfHnflfl)$)$MQLM$@Ht$`H{@1vHC@HHD$`HCPLLݩuLt$`H{@lMMHt$`H{ 1~vHT$`HC HHS0LL蓩uLd$`LS H=))vH=)vH=v)vH=j)vH$H=VH\$8L$(vH==(vH=1(vH=%(vH=(vH|$^LLJH|$0H|$02LLoL IuH$H=H\$8L$H(vH=<(vH=0(vH|$INyINyHOyL$HLt$8NyINyIVOyI7OyHxOyL$HLT$8NyHOyHOyHNyf.fAWAVIAUATUSH(Hw(HG0HWHHO LnHD$Lg8H$H_HL$Ht$L9vwM}IDI@MGPL9t MOPIqSvI MW0L9t M_0IsSvI?IGH9IWI`HrcSvL9uIL9,$wH<$H9|$H;\$tbfDH{@LCPL9t LKPIqSvH{ LS0L9t L[0IsSvH;HCH9tHSH`HrRvH9\$uL9d$tjDI|$@I\$PH9tIL$PHqRvI|$ It$0H9tMl$0IuRvI<$M|$L9Il$I`HurRvL9d$uI>HMfHI^(Ml$I9SIH;HI2RvMIAI9%MIItmItVIt?It(ItH;HQvH;HQvH;HQvH;HQvH;HQvH;HQvH;HvQvI9vxH;H@`QvH{ȾRQvH{оDQvH{ؾ6QvH{(QvH{QvH{ QvH{PvI9wI>IvH([]HA\A]A^A_PvI`I9IL9,$dI`L9d$I>H6H([]A\A]A^A_fDH`H9\$9H;\$H{@LcPL9t HKPHqFPvH{ Hs0H9t Lk0Iu,PvH;L{L9t HkH`HuPvH9\$uH`H9\$uIUUUUUUUAWAVAUATIUSHH(LoHHw(dH%(HD$1HW0H+W8HLLC HL+CH)HIHLHHDHIM9LLSMM)MIM)I$uMt$IEHk0LULUM<$LT$MMt MBLt$IfI A7HL$@uL}0LuB1Ml$(L} Mt$ LLt MLl$IIELDE0H}PLm(B(H}@Mt$@Md$HMMt MLd$IIE>D}PLeHB'HkHHMHfHnfHnHfHnflflK0[@HD$dH+%(HH([]A\A]A^A_@MNHL$DM@L(MerfLqK 6I9MҾHIEMl2I9J<NuLHs(L)IHL4HCHHPH9t H)LuLCH;J4.MvL;LkMA~M,.Ls(LkHIfInflCImHk8HHk@Ht$H} 1uLL$HE HLM0LL蕠uLl$HE Ht$1HAuHT$HEHHULLVuLt$HMyHt$H}@1uL\$HE@HL]PLLuLd$H}@M)IILO4H)L9vL9LuL9H}H)LxuH=WvH=ku&uuH=5vH=)vH|$LIH4IH} I9t Hu0HvdKvH}H9|$t HuHLKvLuH[HH{2KvGvIvLMIvf.HYHt3UHSHGHHCHHuH]f.P yXbasic_string::_M_construct null not valid/__w/ml-builds/ml-builds/xgboost/src/c_api/c_api.ccSaving into deprecated binary model format, please consider using `json` or `ubj`. Model format is default to UBJSON in XGBoost 2.1 if not specified.Current DMatrix type does not support set data.binary saving only supported by SimpleDMatrix/__w/ml-builds/ml-builds/xgboost/src/c_api/../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.htmlp_m->Info().num_col_ <= std::numeric_limits::max()/__w/ml-builds/ml-builds/xgboost/include/xgboost/data.hCheck failed: impl_ != nullptr/__w/ml-builds/ml-builds/xgboost/src/c_api/../common/threading_utils.hSaving model in the UBJSON format as default. You can use file extension: `json`, `ubj` or `deprecated` to choose between formats.Unknown field for Booster feature info:DMatrix has not been initialized or has already been disposed.Check failed: iteration_end == 0Only one of the `ntree_limit` or `iteration_range` can be specified.`ntree_limit` is deprecated, use `iteration_range` instead.Invalid input type for inplace predict.The quantile cut hasn't been generated yet. Unless this is a `QuantileDMatrix`, quantile cut is generated during training.n_numeric == n_features - n_categoriesindptr.back() == vals.size() + mins.size() - n_categoriesFeatureMap feature index exceed boundfeatures.size() <= scores.size()scores.size() % features.size() == 0ulfeatures.size() == scores.size()Check failed: ec == std::errc()Check failed: type >= 1 && type <= 4Check failed: ArrayInterface<1>{iface}.is_contiguousXGQuantileDMatrixCreateFromCallbackXGDeviceQuantileDMatrixCreateFromCallbackstatic_cast*>(handle) ->get() ->Info() .group_ptr_.size() == 0Uslice does not support group structurehalf type is only supported for CUDA input.i_grad.Shape(0) == i_hess.Shape(0)Mismatched shape between the gradient and hessian.i_grad.Shape(1) == i_hess.Shape(1)i_grad.Shape(0) == p_fmat->Info().num_row_Mismatched size between the gradient and training data.gradient and hessian should be on the same device.%02d:%02d:%02d] /__w/ml-builds/ml-builds/xgboost/src/c_api/../data/proxy_dmatrix.hSlicing DMatrix columns is not supported for Proxy DMatrix.Slicing DMatrix is not supported for Proxy DMatrix./__w/ml-builds/ml-builds/xgboost/src/c_api/../data/adapter.hCheck failed: at_first_Cannot reset IteratorAdapter/__w/ml-builds/ml-builds/xgboost/src/c_api/../common/common.hXGBoost version not compiled with GPU support.basic_string::appendOnly dimensional array is valid./__w/ml-builds/ml-builds/xgboost/src/c_api/c_api_utils.hDMatrix/Booster has not been initialized or has already been disposed.USE_CUDAUSE_NCCLUSE_RMMUSE_DLOPEN_NCCLInvalid pointer argument: c_interface_strCheck failed: p_mCheck failed: mCheck failed: c_interfacefnameout_lenout_dptrjson_parametersbufCheck failed: p_outkeyBit fieldBooleanIntegerUnsigned integerFloating pointComplex floating pointTimedeltaDatetimeObjectStringUnicodeOtherInvalid type code: in `typestr' of input array. Or open an issue.dtrainCheck failed: dtrout_indptrout_indicesout_dataCheck failed: page.pagen_threads >= 1out_strjsonubjdeprecatedBUILTIN_PREFETCH_PRESENTMM_PREFETCH_PRESENTUSE_OPENMPGCC_VERSIONDEBUGUSE_FEDERATEDXGDMatrixSetInfoFromInterface2.1.0XGDMatrixSetUIntInfofeature_namefeature_typeout_resultXGBoosterSaveModelToBufferUnknown format: `out_featuresdmatsevnamesc_json_configXGBoosterPredictFromDMatrixiteration_beginiteration_endntree_limittrainingstrict_shapeout_dimout_shapeInplacePredictImplCheck failed: p_predtp_predt->Size() >= n_samplesCheck failed: proxyarray_interfacestr.size() >= 3str[0] == '{'ftypefmapi < data.size()end <= data.size()XGBoosterFeatureScoreimportance_typefeature_mapfeature_namestree_idxidx < names_.size()out_n_featuresout_scoresCheck failed: ejson_strXGDMatrixSetDenseInfoCheck failed: t.CContiguous()Unknown data type1.7.0XGDMatrixCreateFromCSR2.0.0XGDMatrixCreateFromCSRExXGDMatrixCreateFromCSCXGDMatrixCreateFromCSCExXGDMatrixCreateFromURIsilentdata_split_modeXGDMatrixCreateFromCallbackcache_prefixnthreadnextresetCheck failed: _refInvalid handle to ref.max_binarray.valid.Capacity() == 0gradhessgrad_is_cuda == hess_is_cudaXGBoosterTrainOneIterXGBoosterBoostOneIterfloat32float64bool8int32int8int16int64Unknown data table type.falseUnknown global parameters: { syclsycl:cpusycl:gpuUnknown device./__w/ml-builds/ml-builds/xgboost/include/xgboost/context.htԈԈԈӈ4Ԉ yhy8yhyhyhyXyhyxyyhyhyhyhyhyhyhyhyhyhyhyyyhyhyyhyhyyhyhyhy8yhyhyhyhyhyhyXyxyTzz zzzz4zz\zzzztzz,zz4zzTzz|z {zz { {L{{T{{t{{{, {<{ {5{5{L8{:{T={?{tB{E{G{,J{<0{3{4]{l]{_{lb{d{g{j{l{length()read can not have position excceed buffer lengthCheck failed: curr_ptr_ + size <= buffer_size_Check failed: pp_mInvalid DMatrix handleProxy DMatrix cannot return data batch.streamstrides<typestr/__w/ml-builds/ml-builds/xgboost/include/xgboost/json.hInvalid cast, from Missing `version' field for array interfaceOnly version <= 3 of `__cuda_array_interface__' and `__array_interface__' are supported.Missing `typestr' field for array interfaceCheck failed: typestr.size() == 3 || typestr.size() == 4`typestr' should be of format .Missing `shape' field for array interfaceMissing `data' field for array interfaceEmpty data passed in.vector::_M_range_check: __n (which is %zu) >= this->size() (which is %zu)Empty data with non-zero shape.maskj_shape.size() == 1type_length == 1strides.size() == 1Memory should be contiguous.basic_string::at: __n (which is %zu) >= this->size() (which is %zu)mask with bitfield type should be of 1 byte per bitfield.mask with integer type should be of 1 byte per integer.mask must be of integer type or bit field type.get(strides.at(0)) == type_lengthvector::_M_realloc_insertvector::_M_default_appendchunksize == groupsUnknown prediction type:std::accumulate(shape.cbegin(), shape.cend(), static_cast(1), std::multiplies<>{}) == chunksize * rowslearnergradient_boostergblineargbtree_model_paramnum_parallel_treestoiUnknown booster:/__w/ml-builds/ml-builds/xgboost/src/c_api/../common/json_utils.hInvalid type for: ``, expecting one of the: {`}, got: `Argument `` is required for ``.`, Argument `missing` is required.cannot create std::vector larger than max_size()i < D/__w/ml-builds/ml-builds/xgboost/include/xgboost/feature_map.hfid == static_cast(names_.size())unknown feature type, use i for indicator and q for quantityfloatcustom_feature_names.size() == n_featuresIncorrect number of feature names.feature_names.size() == n_featuresfeature_types.size() == n_featuresIncorrect number of feature types.feature_map.Size() == n_featuresout_modelsCheck failed: m == 1 || n == 1j_strides.size() == j_shape.size()stride and shape don't match.Half type is not supported.ptr % alignment == 0Input pointer misalignment.Check failed: mask_it == array.cend() || IsA(mask_it->second)Masked array is not yet supported.n_bits == nShape of bit mask doesn't match data shape. XGBoost doesn't support internal broadcasting.get(array).size() == 1Column: Check failed: IsA(jarray)Size of columns should be the same.Check failed: consistent__Cannot find argument '', Possible Arguments: ---------------- : St11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EESt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EEN4dmlc5ErrorEN4dmlc10ParamErrorEN4dmlc9parameter16FieldAccessEntryEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIiEEiEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIiEEiEEN4dmlc9parameter10FieldEntryIiEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIbEEbEEN4dmlc9parameter10FieldEntryIbEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIfEEfEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIfEEfEEN4dmlc9parameter10FieldEntryIfEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIdEEdEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIdEEdEEN4dmlc9parameter10FieldEntryIdEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIlEElEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIlEElEEN4dmlc9parameter10FieldEntryIlEEN4dmlc6StreamEN4dmlc10SeekStreamEN4dmlc7istream5InBufEN4dmlc7istreamEN7xgboost6common19MemoryFixSizeBufferEN7xgboost6common18MemoryBufferStreamEN4dmlc8DataIterIN7xgboost4data15CSRAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_15CSRAdapterBatchEEEN7xgboost4data10CSRAdapterEN4dmlc8DataIterIN7xgboost4data17DenseAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_17DenseAdapterBatchEEEN7xgboost4data12DenseAdapterEN4dmlc8DataIterIN7xgboost4data17ArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_17ArrayAdapterBatchEEEN7xgboost4data12ArrayAdapterEN4dmlc8DataIterIN7xgboost4data20CSRArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_20CSRArrayAdapterBatchEEEN7xgboost4data15CSRArrayAdapterEN4dmlc8DataIterIN7xgboost4data15CSCAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_15CSCAdapterBatchEEEN7xgboost4data10CSCAdapterEN4dmlc8DataIterIN7xgboost4data20CSCArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_20CSCArrayAdapterBatchEEEN7xgboost4data15CSCArrayAdapterEN4dmlc8DataIterIN7xgboost4data21DataTableAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_21DataTableAdapterBatchEEEN7xgboost4data16DataTableAdapterEN4dmlc8DataIterIN7xgboost4data20ColumnarAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_20ColumnarAdapterBatchEEEN7xgboost4data15ColumnarAdapterEN4dmlc8DataIterIN7xgboost4data16FileAdapterBatchEEEN7xgboost4data12DMatrixProxyEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIjEEjEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIjEEjEEN4dmlc9parameter10FieldEntryIjEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryImEEmEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryImEEmEEN4dmlc9parameter10FieldEntryImEEN7xgboost4data15IteratorAdapterIPvFiS2_PFiS2_15XGBoostBatchCSRES2_ES3_EESt15_Sp_counted_ptrIPN7xgboost7DMatrixELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data12DMatrixProxyELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_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_policyE2EESt15_Sp_counted_ptrIPN7xgboost17BatchIteratorImplINS0_13ExtSparsePageEEELN9__gnu_cxx12_Lock_policyE2EE0001020304050607080910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485868788899091929394959697989900010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899?0C?C/__w/ml-builds/ml-builds/xgboost/src/c_api/coll_c_api.ccCheck failed: !ptr->second.valid()Check failed: res != std::future_status::deferred seconds reached for TrackerFree, killing the tracker./__w/ml-builds/ml-builds/xgboost/src/c_api/../collective/../data/array_interface.hXGBoost is not compiled with federated learning support.Check failed: ptrargsTracker is already running.name_strTime out dmlc_communicatorXGTrackerCreatefederatedrabitUnknown communicator:timeout/__w/ml-builds/ml-builds/xgboost/include/xgboost/collective/socket.hCheck failed: data.Contiguous()/__w/ml-builds/ml-builds/xgboost/src/c_api/../collective/allreduce.h/__w/ml-builds/ml-builds/xgboost/src/c_api/../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/c_api/../collective/allgather.hpP0PSt19_Sp_make_shared_tagSt23_Sp_counted_ptr_inplaceIN7xgboost10collective12RabitTrackerESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEFailed to close /__w/ml-builds/ml-builds/xgboost/include/xgboost/collective/sockTimeout waiting for the tracker./src/c_api/coll_eABroadcast AllgatherV failed, current iteration:/__w/ml-builds/ml-builds/xgboost/src/collective/allgather.ccRing AllgatherV failed, current iterataion:Ring allgather failed, current iteration:/__w/ml-builds/ml-builds/xgboost/src/collective/comm.hCheck failed: sock_.get()Check failed: loop_worker_off < worldsend_seg.size() != 0recv_seg.size() != 0vector::_M_range_insert/__w/ml-builds/ml-builds/xgboost/src/collective/allgather.h*offset.cbegin() == 0Ring scatter reduce failed, current iteration:/__w/ml-builds/ml-builds/xgboost/src/collective/allreduce.ccseg.size() == recv_seg.size()first.size() == data.size()seg_nbytes % sizeof(T) == 0data.size_bytes() % n_bytes_elem == 0/__w/ml-builds/ml-builds/xgboost/src/collective/../data/array_interface.hďˌ̌ʌʌɌ ɌDȌ,ȌȌȌ̌Ring allreduce sRing Allreduce f/__w/ml-builds/ml-builds/xgboost/src/collective/broadcast.ccmask != 0peer != rootbroadcast failedlhs.size() == out.size()Invalid input for reduction./__w/ml-builds/ml-builds/xgboost/src/collective/coll.ccNCCL is required for device communication.@zz@{{0yy}~ЃPЄPX ``P茍((ppxxyyyyz8zPzhzzzxhy(HhЈ@}0X 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_clISt7bit_andIvEtEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt6bit_orIvEtEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt7bit_xorIvEtEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIjEEDaSB_EUlSB_SC_E_jEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clIjEEDaSB_EUlSB_SC_E0_jEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt4plusIvEjEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt7bit_andIvEjEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt6bit_orIvEjEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt7bit_xorIvEjEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clImEEDaSB_EUlSB_SC_E_mEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clIZZNS1_9AllreduceES4_S7_S9_SA_ENKUlSB_E1_clImEEDaSB_EUlSB_SC_E0_mEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt4plusIvEmEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt7bit_andIvEmEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt6bit_orIvEmEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_*ZZN7xgboost10collective4Coll9AllreduceERKNS0_4CommENS_6common4SpanIaLm18446744073709551615EEENS_21ArrayInterfaceHandler4TypeENS0_2OpEENKUlT_T0_E0_clISt7bit_xorIvEmEEDaSB_SC_EUlNS6_IKaLm18446744073709551615EEES7_E_St23enable_shared_from_thisIN7xgboost10collective4CollEEN7xgboost10collective4CollEUnknown algorithm for allgather-Floating point is not supported for bit wise collective operatio/__w/ml-builds/ml-builds/xgboost/src/collective/../common/common.hXGBoost version not compiled with NCCL support.Failed to receive error signal./__w/ml-builds/ml-builds/xgboost/src/collective/protocol.h/__w/ml-builds/ml-builds/xgboost/src/collective/comm.ccAnother worker is running into error.Check failed: !info.host.empty()Failed to connect to the error socket.Failed to send shutdown signalThe communicator is being destroyed without a call to shutdown first. This can lead to undefined behaviour.Bootstrap failed to connect to ring next.Failed to get host names from peers.Failed to get the port from peers.peers[comm.Rank()].port == lportFailed to send init command from worker.Failed to recv init command from tracker.Failed to receive the rank for the next worker.Failed to connect to other workers.Check failed: this->channels_.empty()Rank Task got rank Failed to verify.Invalid verification number. connected to the trackerinet_ntopGot an invalid host name.p.port != -1Failed to send rank.Failed to recv rank.Check failed: workers[r]Failed to listen.world_sizeInvalid world size.Failed to set TCP no delay.Failed to set TCP keeaplive.Failed to call ``: getsockopt(this->Handle(), SOL_SOCKET, SO_DOMAIN, reinterpret_cast(&domain), &len)Unknown IA family.getsockname failed.socketFailed to close the socket.Failed to accept.St23enable_shared_from_thisIN7xgboost10collective4CommEEN7xgboost10collective4CommEN7xgboost10collective8HostCommEN7xgboost10collective9RabitCommEN7xgboost10collective7ChannelE*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7xgboost10collective9RabitComm9BootstrapENSt6chrono8durationIlSt5ratioILl1ELl1EEEEiNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEUlvE3_EEEEEESt15_Sp_counted_ptrIPN7xgboost10collective9TCPSocketELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost10collective4LoopELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost10collective9TCPSocketESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost10collective7ChannelESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEFailed to get soFailed to set socket to non-blocFailed to set tigetsockname failFailed to acceptFailed to send shutdown command Failed to send error command froFailed to connect to the trackerFailed to send init command fromFailed to send print command fro/src/collective/Bootstrap failedFailed to listenFailed to bootstrap the communic/__w/ml-builds/ml-builds/xgboost/src/collective/comm_group.cc/__w/ml-builds/ml-builds/xgboost/src/collective/comm_group.hCheck failed: ctx->IsCUDA()Duplicated parameter:Check failed: comm_Invalid communicator type/__w/ml-builds/ml-builds/xgboost/src/collective/../common/json_utils.hSt15_Sp_counted_ptrIPN7xgboost10collective4CollELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost10collective4CommELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost10collective9RabitCommELN9__gnu_cxx12_Lock_policyE2EEdmlc_tracker_uridmlc_tracker_porInvalid reduce operationInvalid data type/__w/ml-builds/ml-builds/xgboost/src/collective/in_memory_handler.ccFloating point types do not support bitwise operations.KPKK@KŏCheck failed: world_size_ < world_sizeIn memory handler already initialized.In memory handler already shutdown.Check failed: world_size_ > 0: handling requestbasic_string::replace: all requests received: waiting for all clients: sending reply: all replies sent: waiting for current sequence number%s: __pos (which is %zu) > this->size() (which is %zu)_^`Z^dZ@\^`ZdZ@\^`Zin_memory_handle/__w/ml-builds/ml-builds/xgboost/src/collective/loop.ccthis->Block().OK() == this->rc_.OK()Check failed: op.code == Op::kSleepCheck failed: op.sock->NonBlocking()Failed to retrieve socket error.Encountered EOF. The other end is likely closed.Check failed: qcopy.empty() || stop_Exception inside the event loop:Unknown exception inside the event loop.std::future_error: Check failed: !qcopy.empty()Socket error.Invalid socket output.op.off <= op.nop.n != 0vector::reservePoll timeout: seconds.Poll failed, nfds: code:/__w/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/socket.hcannot create std::deque larger than max_size()NSt13__future_base13_State_baseV2ENSt13__future_base7_ResultIvEENSt13__future_base13_State_baseV27_SetterIvvEE*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7xgboost10collective4LoopC4ENSt6chrono8durationIlSt5ratioILl1ELl1EEEEEUlvE_EEEEEESt23_Sp_counted_ptr_inplaceINSt13__future_base13_State_baseV2ESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseIvESaIS1_ELN9__gnu_cxx12_Lock_policyE2EEWorker has stoppPoll error condiInvalid polling Poll hung up on Invalid socket o/__w/ml-builds/ml-builds/xgboost/src/collective/result.cc]: - system error:/__w/ml-builds/ml-builds/xgboost/src/collective/socket.ccCheck failed: !this->IsClosed()str.size() < std::numeric_limits::max()static_cast(conn.Domain()) == static_cast(addr.Domain())): Failed to connect to: Error:Failed to get addr info for: , error: 127.0.0.10.0.0.0::1::Retrying connection to for the time.Failed to connect to Failed to retrieve socket error.Failed to get hoFailed to recv sFailed to start tracker, timeout:/__w/ml-builds/ml-builds/xgboost/src/collective/tracker.ccInvalid initialization sequence.Failed to send init command from tracker.Failed to initialize worker proxy.Failed to get socket flag.Failed to set socket to non-blocking.sendFailed to shutdown socket.Recieved error from [Failed to send error signalFailed to inform worker: for error.dmlc_tracker_uridmlc_tracker_portrecvConnect protocol failed.task_idcmdInvalid port.error_portmsgInvalid print command.Invalid error command.sortbyTrackerpending.size() <= n_workersn_shutdown <= n_workersFailed to get address info:Failed to create socket.10.255.255.255Failed to find IP address.Failed to get sock name.Failed to close socket.127.Failed to bind socket.getsocknameFailed to accept connection.Failed to handle abort.pending.size() < n_workersCheck failed: !runningpending.size() == n_workersn_shutdown >= 0n_shutdown < n_workersInvalid command received.rankPoll error condition:Invalid polling request.Poll hung up on the other end.NSt13__future_base21_Async_state_commonV2EN7xgboost10collective7TrackerEN7xgboost10collective12RabitTrackerE*NSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost10collective12RabitTracker3RunEvEUlvE0_EEEENS5_6ResultEEE*NSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost10collective12RabitTracker3RunEvEUlvE0_EEEENS5_6ResultEEE*ZN7xgboost10collective14GetHostAddressEPNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEUlPP8addrinfoE_*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7xgboost10collective12RabitTracker9BootstrapEPSt6vectorINS5_11WorkerProxyESaIS7_EEEUlvE_EEEEEE*St23_Sp_counted_ptr_inplaceINSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost10collective12RabitTracker3RunEvEUlvE0_EEEENS6_6ResultEEESaISC_ELN9__gnu_cxx12_Lock_policyE2EE*NSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIN7xgboost10collective6ResultEEENS_12_Result_base8_DeleterEENSt6thread8_InvokerISt5tupleIJZNS4_12RabitTracker3RunEvEUlvE0_EEEES5_EE*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZNSt13__future_base17_Async_state_implINS1_IS2_IJZN7xgboost10collective12RabitTracker3RunEvEUlvE0_EEEENS6_6ResultEEC4EOSA_EUlvE_EEEEEENSt13__future_base7_ResultIN7xgboost10collective6ResultEEENaNInfinity0E0@je _vH@0ļ4&k7y؅W4Ngm=`X@xPMJ- yCx(,*42q0/'|!1錠9Y>R$n`F"x|+MraB ydiWC*fJ\)c7]`xxֲK}Yq\Ck 3TgffffffQ~jt*Ǻ"<8b->Nc{-1+x#c^- Knu7X%Y^_GzK`eq]p J&gչ o"4%QttS`؈$C(ӦfHRl ۩#j+vv=IJ+10Q=ѬVZbu)j}և]:1VӾa'miK$!Q㢢P@9j>`KUq݉ [qB1h?(SuYQ!"GMk9X 3D۸N <C.{$~ۃ6/l##ՂF!00010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899/__w/ml-builds/ml-builds/xgboost/src/common/../data/../common/io.h/__w/ml-builds/ml-builds/xgboost/src/common/column_matrix.ccgmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_valw_n_bytes == n_bytesw_n_bytes == remainingbad_malloc: Failed to allocate /__w/ml-builds/ml-builds/xgboost/src/common/../data/../common/ref_resource_view.h bytes.mem_->Size() >= nreinterpret_cast(ptr) % std::alignment_of_v == 0N7xgboost6common14MallocResourceESt23_Sp_counted_ptr_inplaceIN7xgboost6common14MallocResourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE?\\\"\b\f\n\r\t\u%04xYou have manually specified the `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.The tree method `gpu_hist` is deprecated since 2.0.0. To use GPU training, set the `device` parameter to CUDA instead. E.g. tree_method = "hist", device = "cuda" Falling back to prediction using DMatrix due to mismatched devices. This might lead to higher memory usage and slower performance. XGBoost is running on: , while the input data is on: Potential solutions: - Use a data structure that matches the device ordinal in the booster. - Set the device for booster before call to inplace_predict. This warning will only be shown once. Empty dataset at worker: ` is deprecated since, use `` instead.device E.g. device=cpu/cuda/cuda:0/src/common/erro/__w/ml-builds/ml-builds/xgboost/src/common/hist_util.cc/__w/ml-builds/ml-builds/xgboost/src/common/threading_utils.hentries_per_columns.size() == static_cast(n_columns)column_sizes_tloc[i].size() == static_cast(n_columns)entries_per_column.size() == info.num_col_Check failed: offsetsrow_indices.Size() != 0Check failed: !offsetsvector::_M_fill_insert/__w/ml-builds/ml-builds/xgboost/src/common/quantile.hCheck failed: nlevel <= std::max(static_cast(1), static_cast(limit_size * eps))invalid init parameter/__w/ml-builds/ml-builds/xgboost/src/common/hist_util.hUnreachable@)ASortedSketchCont/__w/ml-builds/ml-builds/xgboost/src/common/host_device_vector.ccSize() == other.Size()Size() == other.size()basic_string::substrCheck failed: outFaled to call munmap: close(handle_->fd) != -1Faled to close: pointer_ <= buffer_.size()file://Only local file is supported.Opening fd >= 0Failed to open:ptr != ((void *) -1)Failed to map: /__w/ml-builds/ml-builds/xgboost/src/common/io.ccmunmap(handle_->base_ptr, handle_->base_size) != -1Check failed: (parsed.protocol == "file://" || parsed.protocol.length() == 0)/__w/ml-builds/ml-builds/xgboost/src/common/io.hNot implementedN7xgboost6common16PeekableInStreamEN7xgboost6common15FixedSizeStreamEN7xgboost6common15ResourceHandlerEN7xgboost6common12MmapResourceEN7xgboost6common25AlignedResourceReadStreamEN7xgboost6common22PrivateMmapConstStreamEN7xgboost6common18AlignedWriteStreamEN7xgboost6common22AlignedFileWriteStreamEN7xgboost6common21AlignedMemWriteStreamE/__w/ml-builds/ml-builds/xgboost/src/common/json.cc can not be indexed by string. can not be indexed by Integer./__w/ml-builds/ml-builds/xgboost/include/xgboost/string_view.hCheck failed: ret.ec == std::errc()High precision number is not supported.` is not supported for typed array.NumberNullF32ArrayF64ArrayU8ArrayI32ArrayI64ArrayObject of type , around character position: , "beg <= size_\0Expecting digit Unknown constructch != -1cursor_.Pos(): raw_str_.size():#$($8$H$`$x$$$$##8caaaaaaaaaaaaaaaaacaaabab(b '\Hz\׊/__w/ml-builds/ml-builds/xgboost/include/xgboost/json_io.hOnly UBJSON format can handle f64 array.", got: "EOF"\0"N7xgboost5ValueEN7xgboost10JsonStringEN7xgboost9JsonArrayEN7xgboost10JsonObjectEN7xgboost10JsonNumberEN7xgboost11JsonIntegerEN7xgboost8JsonNullEN7xgboost11JsonBooleanEN7xgboost10JsonReaderEN7xgboost10JsonWriterEN7xgboost9UBJReaderEN7xgboost9UBJWriterEN7xgboost14JsonTypedArrayIfLNS_5Value9ValueKindE7EEEN7xgboost14JsonTypedArrayIdLNS_5Value9ValueKindE8EEEN7xgboost14JsonTypedArrayIhLNS_5Value9ValueKindE9EEEN7xgboost14JsonTypedArrayIiLNS_5Value9ValueKindE10EEEN7xgboost14JsonTypedArrayIlLNS_5Value9ValueKindE11EEE Unknown construcExpecting null v/__w/ml-builds/ml-builds/xgboost/src/common/common.h optional, default=, requiredvalue for Parameter exceed bound [ should be greater equal to should be smaller equal to Required parameter is not presentedInvalid Parameter format for expect but value='/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h*p == ')'Invalid NAN literalOut of range valuepos <= value.length()Out of range value for , value='No conversion could be performed/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.hSome trailing characters could not be parsed: 'key has already been registered in Y@v? L AThe delta term in Pseudo-Huber lPesudoHuberParamphphh0ihhi`h ihi`hjjjjk0kPkpkkkkl/__w/ml-builds/ml-builds/xgboost/src/common/../collective/allreduce.h/__w/ml-builds/ml-builds/xgboost/src/common/categorical.hInvalid categorical value detected. Categorical value should be non-negative, less than total number of categories in training data and less than Maximum cateogry should not be lesser than the total number of categories./__w/ml-builds/ml-builds/xgboost/src/common/quantile.cchessian.size() == info.num_row_group_ptr.back() == hessian.size()weights.size() == info.num_row_Finalize: invalid maximum size, max_size=<Ζ<ΖlϖTϖ<ϖ$ϖϖ|ϖϖ ϖΖΖЖЖ4ііЖЖЖЖЖЖЖdЖ$$,|\|dT<$ddlT<$|dTD$tdT<$ $$D$ t/__w/ml-builds/ml-builds/xgboost/src/common/../data/adapter.hP8D$t\4invalid maximum size max_size=sketch->temp.size < max_size, stemp.sizeINFO: rmax=, sum_total=, naxt_goal=, size=base_rowid < group_ptr.back()Row: is not found in any group.max_cat + 1 >= n_categoriesPushColPagesketch->temp.size <= max_size, stemp.size=HostSketchContainergroup_ptr.size() >= 2group_ptr.back() == n_samplesinfo.weights_.Size() == n_groupsSize of weight must equal to the number of query groups when ranking group is used.Invalid query group structure. The number of rows obtained from group doesn't equal to the number of rows from the data.src.size == 0this->size == 0mingap=, maxgap=, wgap=bug in combineCheck failed: size <= sa.size + sb.size check quantile stats, nbig=, n= srcsize=, maxsize=, range=, chunk=] rmin=, rmax=, wmin=, v=Check failed: nbig < nquantile: too many large chunkCheck failed: a.dataCheck failed: a.data && reduced[fidx].dataCheck failed: reduced[i].dataFailed to get sketch scan.worker_segments.size() >= 1Failed to get sketch.feature_ptr.front() == 0rank_size == totalCheck failed: worker_feature.data()SketchContainerImplcolumns_size_.size() != 0n_threads_ >= 1AllReducen_columns == sketches_.size()num_cuts.size() == 0Number of columns differs across workersMakeCutsp_cuts->cut_values_.HostVector().size() <= std::numeric_limits::max()cut_size > p_cuts->cut_ptrs_.HostVector().back()count <= total_entriesh_weights.size() == batch.Size()Invalid size of sample weight.Check failed: !this->columns_size_.empty()PushRowPagesketches_.size() == n_columns88؟xhP8 hh衚ȡpX@(P೚ȳ($촚ԴܱTǚǚȚȚhȚPȚ@Ț(ȚȚǚǚǚȚȚʚ`ʚ@ʚ ʚʚɚɚɚɚ`ɚ@ؚ@ؚ ښ@ٚ0ٚښښ ؚٚ ٚٚ ؚ@ؚ@ؚؚؚٚٚpٚXٚPښ8ښ ښؚܚܚ8ܚݚݚݚݚۚݚ`ܚݚۚۚۚ@ݚݚݚܚܚܚܚܚ`ܚ@ܚ$lT4dddD$K_o;o:A>/__w/ml-builds/ml-builds/xgboost/src/common/../common/json_utils.hN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIN7xgboost6common15ParamFloatArrayEEES5_EEN4dmlc9parameter10FieldEntryIN7xgboost6common15ParamFloatArrayEEEList of quantiles for quantile lQuantileLossPara/__w/ml-builds/ml-builds/xgboost/src/common/algorithm.hCheck failed: ctx->IsCPU()/__w/ml-builds/ml-builds/xgboost/src/common/random.harray.size() == weights.size()/__w/ml-builds/ml-builds/xgboost/src/common/../collective/../data/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/common/random.ccfeatures.size() > 0Check failed: ctx_tH޹St23_Sp_counted_ptr_inplaceIN7xgboost16HostDeviceVectorIjEESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE߰߰߰߰75//__w/ml-builds/ml-builds/xgboost/src/common/ranking_utils.h can only be used with binary labels.Check failed: label_is_integerWhen using relevance degree as target, label must be either 0 or positive integer.Relevance degress must be lesser than or equal to when the exponential NDCG gain function is used. Set `ndcg_exp_gain` to false to use custom DCG gain./__w/ml-builds/ml-builds/xgboost/src/common/ranking_utils.ccg_rank.size() == sorted_idx.size()Check failed: is_binary%u[-]?Check failed: label_is_validrank.size() == predt.size()enum_back_map_.count(value) != 0UValue not found in enum declaredInvalid Input: '', valid values are: Enum exisit!) Enums: ), long (non-negative)doubleݞ]ݞLxPN4dmlc9parameter10FieldEntryIN7xgboost3ltr10PairMethodEEElambdarank_pair_Method for constlambdarank_num_pNumber of pairs for each sample lambdarank_unbiaUnbiased lambda mart. Use extended IPW to debiaslambdarank_normaWhether to normalize the leaf value for lambda rlambdarank_bias_Lp regularization for unbiased lWhen set to true, the label gain is 2^rel - 1, otherwise it's reHgY?@חA$@K/__w/ml-builds/ml-builds/xgboost/src/common/stats.cct_v.Shape(1) != 0/__w/ml-builds/ml-builds/xgboost/src/common/stats.hCheck failed: alpha >= 0 && alpha <= 1k >= 0E##<=)2??/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./parameter.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././strtonum.hN4dmlc9parameter10FieldEntryIN7xgboost6common27ProbabilityDistributionTypeEEEaft_loss_distribChoice of distribution for the noise term in Accelerated FailureScaling factor used to scale the distribution in Accelerated FaiInvalid thread limit for OpenMP./__w/ml-builds/ml-builds/xgboost/src/common/threading_utils.cclimit >= 1Invalid cgroupv2 file./sys/fs/cgroup/cpu/cpu.cfs_quotapu/cpu.cfs_perioTimer for calls @ us======== Monitor ( ======== did not get stopped properly..A/src/common/time/__w/ml-builds/ml-builds/xgboost/src/common/version.ccfi->Read(&read[0], verstr.size()) == verstr.size()Check failed: fi->Read(&major)Check failed: fi->Read(&minor)Check failed: fi->Read(&patch)Invaid version format in loaded JSON object: Incorrect version format found in binary file. Binary file from XGBoost < 1.0.0 is no longer supported. Please generate it agaibad optional accessddldddLddd$ddddddddddddddddddddddddddddddddddddddddddddddddd8p@/__w/ml-builds/ml-builds/xgboost/src/context.ccBoth `device` and `gpu_id` are specified. Use `device` instead.Check failed: opt_id.has_value()Invalid value for `gpu_id`. Got:Invalid argument for `device`. Expected to be one of the following: - cpu - cuda - cuda: # e.g. cuda:0 - gpu - gpu: # e.g. gpu:0 gpu(:[0-9]+)?|cuda(:[0-9]+)?|cpu|sycl(:cpu|:gpu)?(:-1|:[0-9]+)?sycl(:cpu|:gpu)?(:-1|:[0-9]+)?opt_id.value() <= std::numeric_limits::max()XGBoost is not compiled with CUDA support.new_d.ordinal == this->device_.ordinalthis->device_.ordinal == DeviceOrd::CPUOrdinal()this->device_.ordinal > DeviceOrd::CPUOrdinal()[Internal Error] Unknown parameters passed to the Context {Got: `ContextOrdinal value too large.NULSOHSTXETXEOTENQACKalertbackspacenewlinevertical-tabform-feedcarriage-returnSOSIDLEDC1DC2DC3DC4NAKSYNETBCANEMSUBESCIS4IS3IS2IS1exclamation-markquotation-marknumber-signdollar-signpercent-signampersandapostropheleft-parenthesisright-parenthesisasteriskplus-signcommahyphenperiodonetwothreefourfivesixsevenninesemicolonless-than-signequals-signgreater-than-signquestion-markcommercial-atJSVWYZleft-square-bracketbackslashright-square-bracketcircumflexunderscoregrave-accentzleft-curly-bracketvertical-lineright-curly-brackettildeDELalnumblankcntrlgraphlowerprintpunctupperxdigitUnexpected end of regex when escaping.Unexpected end of regex when reading control code.Unexpected end of regex when ascii character. has not been registered in Alias seedlongrandom_stateseed_per_iterationbooleanstringDevice ordinal.Number of threads to use.n_jobsfail_on_invalid_gpu_idvalidate_parametersRandom number seed during training.Seed PRNG determnisticly via iterator number.Fail with error when gpu_id is invalid.Enable checking whether parameters are used or not.Unexpected escape character.Unexpected end of regex when in an open parenthesis.Invalid special open parenthesis.Unexpected end of regex when in brace expression.Unexpected character in brace expression.Unexpected end of character class.Unexpected end of regex when in bracket expression.Unexpected character class open bracket.^$\.*+?()[]{}|.[\()*+?{|^$.[\*^$.[\()*+?{|^$ .[\*^$ Number of NFA states exceeds limit. Please use shorter regex string, or use smaller brace expression, or make _GLIBCXX_REGEX_STATE_LIMIT larger.Unexpected back-reference in polynomial mode.Back-reference index exceeds current sub-expression count.Back-reference referred to an opened sub-expression.wiWD1|fVA+nZI5 ykYG5"tcN8&u_J:)8""#p#%X%%0%"H&8"&`">l??@L@l@@@>@>\A?Invalid character class.Invalid range in bracket expression.Nothing to repeat before a quantifier.Unexpected token in brace expression.Unexpected end of brace expression.Invalid range in brace expression.Invalid collate element.Invalid equivalence class.Unexpected dash in bracket expression. For POSIX syntax, a dash is not treated literally only when it is at beginning or end.Character is expected after a dash.Unexpected character in bracket expression.Parenthesis is not closed.St19bad_optional_accessN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEES8_EEN4dmlc9parameter10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEESt23_Sp_counted_ptr_inplaceINSt8__detail4_NFAINSt7__cxx1112regex_traitsIcEEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1ELb1EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1EEEww/__w/ml-builds/ml-builds/xgboost/src/data/adapter.hCheck failed: columns_ == data::kAdapterUnknownSize || columns_ == batch.columnsNumber of columns between batches changed from /__w/ml-builds/ml-builds/xgboost/src/data/../common/common.hbad any_castautoZZZ[0[ [P[Zp[@[`[ZP214111041P4p41111111111144114114111511111105P5p,,Ln\r`N<\|d˯ʯϯ ϯ.ͯͯʯȯǯ<ůTï<˯ư3հaհ.װ˰/__w/ml-builds/ml-builds/xgboost/src/data/data.ccUnknown data type for getting meta info.Invalid device ordinal. Data is associated with a different device ordinal than the booster. The device ordinal of the data is: ; the device ordinal of the Booster is: /__w/ml-builds/ml-builds/xgboost/src/data/../collective/../data/array_interface.h/__w/ml-builds/ml-builds/xgboost/src/data/../collective/../data/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/data/../common/threading_utils.hself_offset.size() == other_offset.size()cache_file.find('#') == std::string::nposOnly one `#` is allowed in file path for cache file specification.Check failed: data_split_mode != DataSplitMode::kColColumn-wise data split is not supported for external memory.group_ptr_.size() == weights_.Size() + 1the actual number of rows given by data.Size of weights must equal to number of rows.Size of labels must equal to number of rows.labels_lower_bound_.Size() == num_row_Size of label_lower_bound must equal to number of rows.feature_weights.Size() == num_col_Size of feature_weights must equal to number of columns.labels_upper_bound_.Size() == num_row_Size of label_upper_bound must equal to number of rows.num_nonzero_ <= num_col_ * num_row_base_margin_.Size() % num_row_ == 0Size of base margin must be a multiple of number of rows.All feature_types must be one of {int, float, i, q, c}.Meta info like label or weight can not have missing value.Check failed: t_out.CContiguous()Check failed: strm->Read(&name)Check failed: strm->Read(&type_val)Check failed: type == expected_typeCheck failed: strm->Read(&is_scalar)Check failed: strm->Read(field)Check failed: strm->Read(&shape.first)Check failed: strm->Read(&shape.second)Number of columns is expected to be 1.transpose.offset.Size() == num_columns + 1this->num_col_ == that.num_col_Number of columns must be consistent across batches.this->base_margin_.Size() % this->num_row_ == 0Incorrect size of base margin vector. must be equal to number of columns.Check failed: this->base_margin_.Size() % this->num_row_ == 0Incorrect size for base margin.this->labels.Size() % this->num_row_ == 0Label contains NaN, infinity or a value too large./__w/ml-builds/ml-builds/xgboost/src/data/validation.hCheck failed: valid_query_group`qid` must be sorted in non-decreasing order along with data.Weights must be positive values.Feature weight must be greater than 0.Check failed: strm->Read(&(shape[i]))Check failed: strm->Read(&field)Binary DMatrix generated by XGBoost: Please process and save your data in current version: Check failed: fi->Read(&num_field)MetaInfo: insufficient number of fields (expected at least fields, but the binary file only contains MetaInfo: the given binary file contains extra fields which will be ignored.`H`H JJIIIIhIHI(IIjj0llkkkkkxk`k@kplplnmmmmmpmPm0mm@t@tvuuuMupttupqqsXrHrrrpqrrrpqqqssxs`sPs8s ssrsxxx yyzzwzzzwww@zzzyyyyxyzPy:W!큱|O|}}`~~P@} 0}}}@ pPXЅpX`Ȇx`@8싱DċPЌbase_marginlabel_lower_boundlabel_upper_boundfeature_weightsUnknown float field name: group_ptrUnknown uint32 field name: self_data.size(): other_data.size(): beg <= data.size()ptr < offset.size() matrix with entries loaded from Unknown feature info: group_ptr_.back() == num_row_weights_.Size() == num_row_labels.Shape(0) == num_row_field_cnt == kNumFieldWrong number of fieldsMetaInfo: Invalid format for name == expected_name Expected field: , got: Expected field of type: got field type: Check failed: is_scalarExpected field to be a scalar; got a vectorCheck failed: !is_scalar to be a vector; got a scalarshape.second == 1that.group_ptr_.size() != 0result.size() == n_columnsLength of Incorrect size for labels.Check failed: validInvalid group structure.qidCheck failed: non_decUnknown key for MetaInfo: size == this->num_col_Check failed: infoUnknown feature info name: to be a tensor; got a scalar is no longer supported. again.major >= 1minor >= 6MetaInfo: invalid formatnum_field >= expectedfields.)num_rownum_colnum_nonzerolabelslabels_lower_boundlabels_upper_boundfeature_types/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.hCheck failed: curr_exce_Check failed: page_/__w/ml-builds/ml-builds/xgboost/src/data/../data/adapter.h䑱t\Check failed: lock_.try_lock()Multiple threads attempting to use Sparse DMatrix./__w/ml-builds/ml-builds/xgboost/include/xgboost/linalg.hthis->Data()->Size() == detail::CalcSize(this->shape_)Inconsistent size after modification.shape[i] == r.Shape(i)key >= builder_base_row_offset@ı@ııııhıhű±Xű(ű@ű±(±(±hƱHƱ(ƱƱűűxűPűűƱXͱXͱͱͱ8ααααHαXαpααH˱H˱бϱϱϱϱXϱ8ϱϱαα(߱x߱߱߱8ݱޱ||\| ,Lt,TtCheck failed: !cache_info_->written/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_writer.hUnknown format type format.front() == '.'wb MB written in /__w/ml-builds/ml-builds/xgboost/src/data/../collective/allreduce.hInput data contains `inf` or a value too large, while `missing` is not set to `inf`/__w/ml-builds/ml-builds/xgboost/src/data/../data/proxy_dmatrix.hUnknown type: Check failed: !at_end_n_prefetch_batches > 0total batches:Waitn_prefetch_batches <= kPrefetchesfetch_it < cache_info_->offset.size()std::count_if(ring_->cbegin(), ring_->cend(), [](auto const& f) { return f.valid(); }) == n_prefetch_batchesSparse DMatrix assumes forward iteration.Check failed: !(*ring_)[count_].valid()cache_info_->offset.size() == n_batches_ + 1count_ == n_batches_Check failed: proxy_this->count_ >= 1source_->Iter() == this->count_Check failed: fmt->Read(page.get(), fi.get())St19__shared_ptr_accessIN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt19__shared_ptr_accessIN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt19__shared_ptr_accessIN7xgboost4data15ColumnarAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt12__shared_ptrIN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt12__shared_ptrIN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt12__shared_ptrIN7xgboost4data15ColumnarAdapterELN9__gnu_cxx12_Lock_policyE2EEN7xgboost10SparsePageEN7xgboost7DMatrixEN7xgboost4data11FileAdapterESt12bad_any_castSt10shared_ptrIN7xgboost4data15CSRArrayAdapterEESt10shared_ptrIN7xgboost4data12ArrayAdapterEESt10shared_ptrIN7xgboost4data15ColumnarAdapterEEN7xgboost17BatchIteratorImplINS_11EllpackPageEEEN7xgboost4data20SparsePageSourceImplINS_11EllpackPageEEEN7xgboost4data18PageSourceIncMixInINS_11EllpackPageEEEN7xgboost4data17EllpackPageSourceENSt13__future_base7_ResultISt10shared_ptrIN7xgboost10SparsePageEEEEZN7xgboost6common10ThreadPool6SubmitIZNS_4data20SparsePageSourceImplINS_10SparsePageEE9ReadCacheEvEUlvE_St10shared_ptrIS5_EEEDaOT_EUlvE_St15_Sp_counted_ptrIPN7xgboost6common12MmapResourceELN9__gnu_cxx12_Lock_policyE2EENSt13__future_base13_State_baseV27_SetterISt10shared_ptrIN7xgboost10SparsePageEEOS5_EESt23_Sp_counted_ptr_inplaceIN7xgboost10SparsePageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseISt10shared_ptrIN7xgboost10SparsePageEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EE OOOOAAGGGG/src/data/./sparse_page_source.hlabels_lower_boulabels_upper_bouP?/__w/ml-builds/ml-builds/xgboost/src/data/ellpack_page.ccInternal Error: XGBoost is not compiled with CUDA but EllpackPage is required/__w/ml-builds/ml-builds/xgboost/src/data/file_iterator.ccOnly one `#` is allowed in file path for cachefile specificationURI parameter `format` is required for loading text data: filename?format=csvCheck failed: std::getline(is, kv.first, '=')Check failed: std::getline(is, kv.second)Check failed: parser_name_args_cache.size() <= 2name_args.size() == 2Invalid uri argument format for key in arg for value in arg ,,\ ,LllL, 캴Ժ L<ܿܽ,쿴ܽ|dL4ܿ´´|Ĵ\ĴDĴ,ĴĴôôôôôĴĴƴƴ|ƴ\ƴDƴ,ƴƴŴŴŴ/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index.cc/__w/ml-builds/ml-builds/xgboost/src/data/../common/hist_util.h/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index.hCheck failed: this->data.empty()Check failed: resource->Type() == common::ResourceHandler::kMallochit_count.size() == n_bins_totalCheck failed: p_fmat->SingleColBlock()Check failed: columns_n_bytes >= this->data.size()Check failed: malloc_resourcerow_ptr.size() == 0Check failed: !sorted_sketch/__w/ml-builds/ml-builds/xgboost/src/data/../common/io.h/__w/ml-builds/ml-builds/xgboost/src/data/../common/ref_resource_view.h/__w/ml-builds/ml-builds/xgboost/src/data/../common/column_matrix.hCheck failed: storage.Resource()->Type() == ResourceHandler::kMalloc[Internal Error]: Cannot grow the vector when external memory is used.m_size >= storage.size()Check failed: resourcenum_nonzeros_.size() == n_features22433|4l4d2L4<4\4d2Iter()cuts_.Values().size() != 0N7xgboost17BatchIteratorImplINS_16GHistIndexMatrixEEEN7xgboost4data20SparsePageSourceImplINS_16GHistIndexMatrixEEEN7xgboost4data18PageSourceIncMixInINS_16GHistIndexMatrixEEEN7xgboost4data23GradientIndexPageSourceENSt13__future_base7_ResultISt10shared_ptrIN7xgboost16GHistIndexMatrixEEEEZN7xgboost6common10ThreadPool6SubmitIZNS_4data20SparsePageSourceImplINS_16GHistIndexMatrixEE9ReadCacheEvEUlvE_St10shared_ptrIS5_EEEDaOT_EUlvE_NSt13__future_base13_State_baseV27_SetterISt10shared_ptrIN7xgboost16GHistIndexMatrixEEOS5_EESt15_Sp_counted_ptrIPN7xgboost16GHistIndexMatrixELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost16GHistIndexMatrixESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseISt10shared_ptrIN7xgboost16GHistIndexMatrixEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EE/src/data/sparse@p0Pp PPpX@(`@ PPh@ h@pP0``0pP0x x  x X 8  @@pX8 @@pX8 @@pX8 ## %t$G$$##j##`! !!P! !p"P"8"""!!!!"(())h)H)0)))(((0303&54a454 4/333/00111110p10100.0.2p2X282 221112;;= =<<<085< Info().num_col_ == n_featuresInvalid ref DMatrix, different number of features.page.row_ptr.size() == h_offset.size()/__w/ml-builds/ml-builds/xgboost/src/data/../common/../data/../common/hist_util.hInconsistent number of columns.Check failed: std::none_of(column_sizes.cbegin(), column_sizes.cend(), [&](auto f) { return f > accumulated_rows; })Something went wrong during iteration.Data must has at least 1 column.accumulated_rows == Info().num_row_this->ghist_->Features() == Info().num_col_proxy->Info().labels.Size() == 0Iterative DMatrix must have at least 1 batch.`@ X pP0`@ Ph@ `8``0pP0pX@0`@pP8 pP0xx`@(`@ hhpP0K U | XXpX@ @ @ 0 ` @ k[7P0pP0`@ X [pK'@ `@ !P!0!! p H %% &&[&p'K'#'%''###@% %%$$$$`$@$ $'')P)0))((((p(H(/__w/ml-builds/ml-builds/xgboost/src/data/simple_batch_iterator.hCheck failed: page_ != nullptr/__w/ml-builds/ml-builds/xgboost/src/data/iterative_dmatrix.hSlicing DMatrix is not supported for Quantile DMatrix.Slicing DMatrix columns is not supported for Quantile DMatrix.//1x1`1H101110116698888x8`8H8@99h=h=????p?X?@? ? @?Check failed: proxy_handleInvalid proxy handle.Check failed: typedYY[[p[H[([[ZZZZx`x`aaaahaHa(aa``HbHbcccxcXc8ccbbbparam.max_bin == batch_.max_binInconsistent `max_bin`. `max_bin` should be the same across different QuantileDMatrix, and consistent with the Booster being trained.Check failed: !param.regen && param.hess.empty()Only `hist` and `gpu_hist` tree method can use `QuantileDMatrix`.Not implemented for `QuantileDMatrix`.Check failed: refCheck failed: p_cutsn_features == num_cols()n_features >= 1h_ft.size() == n_ftCheck failed: p_sketchh_ft.size() == n_featuresrbegin == Info().num_row_/__w/ml-builds/ml-builds/xgboost/src/data/../common/../data/gradient_index.hCheck failed: !std::isnan(sparse_thresh)۷۷ݷݷtݷ\ݷLݷ<ݷ$ݷ ݷܷܷt\<| \ D ,   | l \ D ,  l~l~\<$ |||lL4 ܕĕ|\D,쫸ԫ|¸\¸D¸,¸¸¸St14default_deleteIN7xgboost16GHistIndexMatrixEEN7xgboost4data16IterativeDMatrixEN7xgboost4data23SimpleBatchIteratorImplINS_16GHistIndexMatrixEEEN7xgboost17BatchIteratorImplINS_13ExtSparsePageEEEN7xgboost4data23SimpleBatchIteratorImplINS_13ExtSparsePageEEEN7xgboost4data23SimpleBatchIteratorImplINS_11EllpackPageEEESt19_Sp_counted_deleterIPN7xgboost16GHistIndexMatrixESt14default_deleteIS1_ESaIvELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost13ExtSparsePageESaIS1_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: p_fmatFailed to fallback.Check failed: on_hostNot implemented on device.ԸӸ@ָӸӸӸָӸָ׸ӸӸӸӸӸӸӸӸӸӸӸ0׸p׸ӸӸظӸӸHظӸӸӸظӸӸӸӸӸӸظٸSt15_Sp_counted_ptrIPN7xgboost4data15ColumnarAdapterELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2EEUnsigned integerComplex floatingCheck failed: r.Initialized()Generating new Ellpack page.param.max_bin >= 2invalid input file formattmagic == kMagic/__w/ml-builds/ml-builds/xgboost/src/data/../common/error_msg.hSample size too large for the current updater. Maximum number of samples:. Consider using a different updater or tree_method./__w/ml-builds/ml-builds/xgboost/src/data/batch_utils.hBatch parameter is not initialized./__w/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.ccbatch_param_.max_bin == param.max_binCheck failed: !detail::RegenGHist(batch_param_, param)Inconsistent sparse threshold.Generating new Gradient Index.batch_param_.hess.data() == param.hess.data()Check failed: in_stream->Read(&tmagic)invalid format, magic number mismatch/__w/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.h/__w/ml-builds/ml-builds/xgboost/src/data/../collective/allgather.hCheck failed: (std::is_same::value || std::is_same::value)Expecting CSCAdapterN7xgboost7CSCPageEN7xgboost13SortedCSCPageEN7xgboost4data13SimpleDMatrixEN7xgboost17BatchIteratorImplINS_10SparsePageEEEN7xgboost4data23SimpleBatchIteratorImplINS_10SparsePageEEEN7xgboost17BatchIteratorImplINS_7CSCPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_7CSCPageEEEN7xgboost17BatchIteratorImplINS_13SortedCSCPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_13SortedCSCPageEEESt15_Sp_counted_ptrIPN7xgboost7CSCPageELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost13SortedCSCPageELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost11EllpackPageELN9__gnu_cxx12_Lock_policyE2EE/src/data/simpleThe total number of elements should be multiple of the number of/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.ccCheck failed: sparse_page_source_Check failed: ghist_index_source_.row.pageCheck failed: iter_.Next()Must have at least 1 batch.-rinfo_.num_col_ != 0this->Info().num_col_ != 0.sorted.col.page.gradient_index.pagecuts.Values().size() != 0/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_dmatrix.hSlicing DMatrix columns is not supported for external memory.Slicing DMatrix is not supported for external memory./__w/ml-builds/ml-builds/xgboost/src/data/./../common/common.h/__w/ml-builds/ml-builds/xgboost/src/data/./proxy_dmatrix.hCouldn't remove external memory cache file ; you may want to remove it manuallyCan not obtain a single CSR page for external memory DMatrixCheck failed: kv.secondthis->page_->Size() == n_features_this->page_->data.Size() == csr->data.Size()Make cache:N7xgboost4data20SparsePageSourceImplINS_10SparsePageEEEN7xgboost4data16SparsePageSourceEN7xgboost4data20SparsePageSourceImplINS_7CSCPageEEEN7xgboost4data18PageSourceIncMixInINS_7CSCPageEEEN7xgboost4data13CSCPageSourceEN7xgboost4data20SparsePageSourceImplINS_13SortedCSCPageEEEN7xgboost4data18PageSourceIncMixInINS_13SortedCSCPageEEEN7xgboost4data19SortedCSCPageSourceEN7xgboost4data17SparsePageDMatrixENSt13__future_base7_ResultISt10shared_ptrIN7xgboost7CSCPageEEEENSt13__future_base7_ResultISt10shared_ptrIN7xgboost13SortedCSCPageEEEEN7xgboost16GHistIndexMatrixEZN7xgboost6common10ThreadPool6SubmitIZNS_4data20SparsePageSourceImplINS_7CSCPageEE9ReadCacheEvEUlvE_St10shared_ptrIS5_EEEDaOT_EUlvE_ZN7xgboost6common10ThreadPool6SubmitIZNS_4data20SparsePageSourceImplINS_13SortedCSCPageEE9ReadCacheEvEUlvE_St10shared_ptrIS5_EEEDaOT_EUlvE_NSt13__future_base13_State_baseV27_SetterISt10shared_ptrIN7xgboost7CSCPageEEOS5_EENSt13__future_base13_State_baseV27_SetterISt10shared_ptrIN7xgboost13SortedCSCPageEEOS5_EESt15_Sp_counted_ptrIPN7xgboost4data5CacheELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data23GradientIndexPageSourceELN9__gnu_cxx12_Lock_policyE2EENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7xgboost6common10ThreadPoolC4EiEUlvE_EEEEEESt23_Sp_counted_ptr_inplaceIN7xgboost4data16SparsePageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data13CSCPageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data19SortedCSCPageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost7CSCPageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseISt10shared_ptrIN7xgboost7CSCPageEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost13SortedCSCPageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceISt7promiseISt10shared_ptrIN7xgboost13SortedCSCPageEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EE/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_raw_format.ccCheck failed: page.offset.Size() != 0 && offset_vec[0] == 0offset_vec.back() == page.data.Size()Raw binary data format.page->offset.Size() != 0UInvalid SparsePage fileN7xgboost4data16SparsePageFormatINS_10SparsePageEEEN7xgboost4data19SparsePageRawFormatINS_10SparsePageEEEN7xgboost4data16SparsePageFormatINS_7CSCPageEEEN7xgboost4data19SparsePageRawFormatINS_7CSCPageEEEN7xgboost4data16SparsePageFormatINS_13SortedCSCPageEEEN7xgboost4data19SparsePageRawFormatINS_13SortedCSCPageEEE*N7xgboost4dataL26__make_SparsePageFmt_raw__MUlvE_E*N7xgboost4dataL23__make_CSCPageFmt_raw__MUlvE_E*N7xgboost4dataL29__make_SortedCSCPageFmt_raw__MUlvE_Egpu_coord_descentLinear booster does not support prediction range.Linear booster, implement generalized linear model./__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 the current booster.Slice is not supported by the current booster.model/__w/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.hfi->Read(¶m_, sizeof(param_)) == sizeof(param_)DoBoost`gblinear`Check failed: !p_fmat->Info().HasCategorical() doesn't support categorical features.layer_begin == 0GBLinearTrainParamget(in["name"]) == "gblinear"/__w/ml-builds/ml-builds/xgboost/src/gbm/../common/threading_utils.hCheck failed: !model_.weight.empty()gblinear doesn't support number of trees for feature importance.gblinear only has `weight` defined for feature importance.Model is not initializedCheck failed: trees.empty()importance_type == "weight"PredictBatchInternalbase_margin.Size() == nsize * ngroup { "bias": [ ], "weight": [ ] }bias: weight: shotguntolerancemax_row_perbatchMaximum rows per batch.Update algorithm for linear model. One of shotgun/coord_descentStop if largest weight update is smaller than this number.gblinear_train_paramCheck failed: this->updater_/__w/ml-builds/ml-builds/xgboost/src/gbm/../common/common.hLoading configuration on a CPU only machine. Changing updater to `coord_descent`.device="cuda", updater="coord_descent"GBLinearN7xgboost5ModelEN7xgboost12ConfigurableEN7xgboost15GradientBoosterEN7xgboost3gbm8GBLinearE*N7xgboost3gbmL36__make_GradientBoosterReg_GBLinear__MUlPKNS_17LearnerModelParamEPKNS_7ContextEE_Eboosted_roundsN7xgboost3gbm13GBLinearModelEDeprecatedGBLinedeprecated_num_fint (non-negativdeprecated_num_oUnknown gbm type /__w/ml-builds/ml-builds/xgboost/src/gbm/gbm.cch_tmp.Size() == h_in.Size()Update tree leafCheck failed: gpu_predictor_Check failed: cpu_predictor_out_preds->version == 0Invalid number of trees.CPU implementation is usedUnknown device type:Check failed: p_gbtreeend != beginEmpty slice is not allowed.Not all trees are updated, GBTreeModelParamDartTrainParamGBTreeTrainParamgbtree_train_paramspecified_updaterUpdater: `` n_out % gpair->Size() == 0gpair->Size() == n_outCheck failed: ctx_->IsCPU()BoostNewTreesn_groups != 0grow_quantile_histmakergrow_gpu_histgrow_histmakergrow_gpu_approxcpu_predictorUsing tree method: grow_colmaker,pruneUnknown tree_method: `unreachableTree booster, dart./__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree.cc/__w/ml-builds/ml-builds/xgboost/src/gbm/../tree/../common/threading_utils.hCheck failed: !updaters_.empty()model_.param.num_parallel_tree == trees.size()model_.param.num_parallel_tree == 1Boosting random forest is not supported for current objective.Check failed: !trees.front()->IsMultiTarget() support for multi-target tree is not yet implemented.trees.size() == model_.param.num_parallel_tree/__w/ml-builds/ml-builds/xgboost/src/gbm/../data/proxy_dmatrix.htree_end <= model_.trees.size()The requested feature doesn't have SYCL specific implementation yet. Inplace predict accepts only DMatrixProxy as input.Unknown data type for inplace prediction:get(in["name"]) == "gbtree"Check failed: this->model_.learner_model_param->Initialized()this->model_.trees_to_update.size() == this->model_.trees.size() trees remain. Slice the model before making update if you only want to update a portion of trees.out_model.iteration_indptr.front() == 0Check failed: !updaters_.front()->CanModifyTree()can not be used to create new trees. Set `process_type` to `update` if you want to update existing trees.Check failed: up->CanModifyTree()can not be used to modify existing trees. Set `process_type` to `default` if you want to build new trees.model_.trees.size() < model_.trees_to_update.size()No more tree left for updating. For updating existing trees, boosting rounds can not exceed previous training roundsMismatching size between number of rows from input data and size of gradient vector.Check failed: tparam_.tree_method == TreeMethod::kHist || tparam_.tree_method == TreeMethod::kAutoOnly the hist tree method is supported for building multi-target trees with vector leaf.GPU is not yet supported for vector leaf.Current objective doesn't support external memory.in_gpair->Size() % n_groups == 0Umust have exactly ngroup * nrow gpairsThe `exact` tree method is not supported on GPU. Loading from a raw memory buffer (like pickle in Python, RDS in R) on a CPU-only machine. Consider using `save_model/load_model` instead. See: https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html for more details about differences between saving model and serializing. Changing `tree_method` to `hist`./__w/ml-builds/ml-builds/xgboost/src/gbm/../common/error_msg.hIf you are loading a serialized model (like pickle in Python, RDS in R) or configuration generated by an older version of XGBoost, please export the model by calling `Booster.save_model` from that version first, then load it back in current version. See: https://xgboost.readthedocs.io/en/stable/tutorials/saving_model.html for more details about differences between saving model and serializing. Changing updater from `grow_gpu_hist` to `grow_quantile_histmaker`.Tree booster, gradient boosted trees./__w/ml-builds/ml-builds/xgboost/src/gbm/../tree/../common/common.hweight_drop/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.hiteration_indptr.size() == 1/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree.hCheck failed: !model.iteration_indptr.empty()end <= model.BoostedRounds()Out of range for tree layers.tree_begin <= tree_endstep >= 1out_l == n_layerstree_begin == 0Predict interaction contribution supports only iteration end: (0, n_iteration), using model slicing instead.Predict contribution supports only iteration end: (0, n_iteration), using model slicing instead.Predict leaf supports only iteration end: (0, n_iteration), use model slicing instead.get(in["name"]) == "dart"Check failed: !this->model_.learner_model_param->IsVectorLeaf()p_out_preds->predictions.Size() == predts.predictions.Size()Check failed: predictori >= p_out_preds->versionCheck failed: successUnsupported data type for inplace predict.predts.predictions.Size() == p_out_preds->predictions.Size()Check failed: p_dartCheck failed: p_dart->weight_drop_.empty()Check failed: tree_param_.GetInitialised()drop trees, weight = num_treesNumber of parallel trees constructed during each iteration. This option is used to support boosted random forest.sample_typeuniformweightednormalize_typeforestrate_dropone_dropskip_dropDifferent types of sampling algorithm.Different types of normalization algorithm.Fraction of trees to drop during the dropout.Whether at least one tree should always be dropped during the dropout.Probability of skipping the dropout during a boosting iteration.updater_seqTree updater sequence.process_typedefaultupdatetree_methodexactWhether to run the normal boosting process that creates new trees, or to update the trees in an existing model.Choice of tree construction method.dart_train_paramռ׼Zؼռؼ׼*N7xgboost3gbmL34__make_GradientBoosterReg_GBTree__MUlPKNS_17LearnerModelParamEPKNS_7ContextEE_E*N7xgboost3gbmL32__make_GradientBoosterReg_Dart__MUlPKNS_17LearnerModelParamEPKNS_7ContextEE_Eidx <= total_n_treesInvalid tree index.total_gaintotal_coverUnknown feature importance type, expected one of: {"weight", "total_gain", "total_cover", "gain", "cover"}, got: N4dmlc9parameter10FieldEntryIN7xgboost10TreeMethodEEEN4dmlc9parameter10FieldEntryIN7xgboost15TreeProcessTypeEEEN7xgboost3gbm6GBTreeEN7xgboost3gbm4DartE?A;Number of features used for training and predict/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.ccparam.num_trees == static_cast(trees.size())model.trees.size() == model.param.num_treesmodel.tree_info.size() == model.param.num_treesmodel.iteration_indptr.back() == model.param.num_treesCheck failed: !iteration_indptr.empty()iteration_indptr.back() == param.num_treesparam.num_trees == static_cast(trees.size())fi->Read(¶m, sizeof(param)) == sizeof(param)fi->Read(dmlc::BeginPtr(tree_info), sizeof(int32_t) * param.num_trees) == sizeof(int32_t) * param.num_treestrees_json.size() == param.num_treestree_info_json.size() == param.num_treeslayer_trees != 0GBTree: invalid model fileiteration_indptrN7xgboost3gbm11GBTreeModelEgbtree_model_pariteration_indptrFlag to print out detailed breakdown of runtime.Whether to use RAPIDS Memory Manager to allocate GPU memory in XGlobalConfiguratmulti-target-multi-class is not yet supported. Output classes:Check failed: std::as_const(base_score_).Data()->HostCanRead()Model is not yet initialized (not fitted).Check failed: base_score_.Data()->HostCanRead()Check failed: base_score_.Data()->DeviceCanRead()base_score_.Data()->DeviceCanRead() == that.base_score_.Data()->DeviceCanRead()/__w/ml-builds/ml-builds/xgboost/src/learner.ccCheck failed: !this->need_configuration_/__w/ml-builds/ml-builds/xgboost/include/xgboost/objective.hmultioutput is not supported by the current objective function/__w/ml-builds/ml-builds/xgboost/src/collective/../data/../common/error_msg.h, output targets:base_score_.Size() == 1LearnerModelParamLegacyLearnerTrainParamCheck failed: ret.ec == std::errc{}num_featurenum_classnum_targetboost_from_averageCheck failed: learner_model_param_.Initialized()learner_model_param_.BaseScore(this->Ctx()).Size() != 0ModelConfig/__w/ml-builds/ml-builds/xgboost/src/collective/broadcast.hCheck failed: std::equal(data.cbegin(), data.cend(), sync.cbegin())Different model parameter across workers./__w/ml-builds/ml-builds/xgboost/src/collective/allreduce.hCall Configure before saving model.learner_model_paramobjectiveattributeslearner_model_param_.num_feature == p_fmat->Info().num_col_Number of columns does not match number of features in booster.learner_model_param_.num_feature >= p_fmat->Info().num_col_/__w/ml-builds/ml-builds/xgboost/include/xgboost/cache.hqueue_.size() == container_.size()/__w/ml-builds/ml-builds/xgboost/src/collective/aggregator.hGlobal bias of the model.int (non-negative)Number of features in training data, this parameter will be automatically detected by learner.Number of class option for multi-class classifier. By default equals 0 and corresponds to binary classifier.Number of output targets. Can be set automatically if not specified.Whether we should calculate the base score from training data.disable_default_eval_metricreg:squarederrormulti_strategyone_output_per_treemulti_output_treeFlag to disable default metric. Set to >0 to disableGradient booster used for training.Objective function used for obtaining gradient.Strategy used for training multi-target models. `multi_output_tree` means building one single tree for all targets.Check failed: that.lock_.try_lock()Check failed: !this->learner_model_param_.IsVectorLeaf()Please use JSON/UBJ format for model serialization with multi-output models.feature names and feature types are being disregarded, use JSON/UBJSON format instead.;metricsbinfmulti:softprobnum_output_groupmulti:softmaxcount:poisson0.7learner_train_paramgeneric_paramCheck failed: it != container_.cend()remained.size() + expired.size() == container_.size()Check failed: matrix.first.ptrCheck failed: !matrix.second.ref.expired()Unfortunately, XGBoost does not support data matrices with 0 feature is supplied. Are you using raw Booster interface?n_features <= max_n_features features or greatermparam_.num_feature != 0Check failed: this->obj_Inconsistent labels.Check failed: n_targets == t || 1 == tCheck failed: n_targets == 1 || n_targets == mparam_.num_targetInconsistent configuration of num_target. Configuration result from input data:, configuration from parameter:Check failed: tparam_.GetInitialised()learner_model_param_.BaseScore(Ctx()).Size() != 0base_score.Size() == 1Check failed: !std::isnan(mparam_.base_score)Check failed: !std::isinf(mparam_.base_score)Check failed: IsA(in)Invalid version string in configget(objective_fn["name"]) == tparam_.objectiveFound JSON model saved before XGBoost 1.6, please save the model using current version again. The support for old JSON model will be discontinued in XGBoost 2.3.Invalid parameter "" contains whitespace. Parameters: { ", } are not used. Configurecontainer_.size() < max_size__Map_base::atmultiple_predictions <= 1Check failed: gbm_ != nullptrPerform one kind of prediction at a time.Predict must happen after Load or configurationthis->learner_model_param_.OutputLength() == in_gpair->Shape(1)The number of columns in gradient should be equal to the number of targets/classes in the model.UpdateOneIterPredictRawPredictionsGetGradientGradientsLearnerCONFIG-offset:this->learner_model_param_.num_feature != 0out_impl->learner_model_param_.num_feature == this->learner_model_param_.num_featureout_impl->learner_model_param_.num_feature != 0begin >= 0best_iterationbest_scoreEvalOneIterUnsupported prediction type:fixed_size->Read(&buffer[0], size) == sizebs64header != "bs64"fp.Read(&header[0], 4) == 4UInvalid model formatcount_poisson_max_delta_stepmulti: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)data_.Size() == detail::CalcSize(shape_)Loading model from XGBoost < 1.0.0, consider saving it again for improved compatibilityInvalid serialization file.sz > 0fp.Read(&header[0], header.size()) == serialisation_header_.size()Check failed: header == serialisation_header_fp.Read(&sz, sizeof(sz)) == sizeof(sz)N4dmlc12SerializableEN7xgboost7LearnerEN4dmlc9parameter10FieldEntryIN7xgboost13MultiStrategyEEEN7xgboost20LearnerConfigurationEN7xgboost9LearnerIOEN7xgboost11LearnerImplESt23_Sp_counted_ptr_inplaceIN7xgboost20PredictionCacheEntryESaIS1_ELN9__gnu_cxx12_Lock_policyE2EEUnknown linear updater /__w/ml-builds/ml-builds/xgboost/src/linear/linear_updater.ccLearning rate ofL2 regularizatioL1 regularizatiofeature_selectorFeature selection or ordering meLinearTrainParamUpdate linear model according to coordinate descent algorithm./__w/ml-builds/ml-builds/xgboost/src/linear/../common/threading_utils.hUpdateFeatureCoordinateParam/__w/ml-builds/ml-builds/xgboost/src/linear/updater_coordinate.ccSave config for CPU updater./__w/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.hunknown coordinate selector: HN7xgboost13LinearUpdaterEN7xgboost6linear15FeatureSelectorEN7xgboost6linear21CyclicFeatureSelectorEN7xgboost6linear22ShuffleFeatureSelectorEN7xgboost6linear21RandomFeatureSelectorEN7xgboost6linear21GreedyFeatureSelectorEN7xgboost6linear22ThriftyFeatureSelectorEN7xgboost6linear17CoordinateUpdaterE*N7xgboost6linearL43__make_LinearUpdaterReg_CoordinateUpdater__MUlvE_EThe number of top features to select in 'thrifty' feature_selector. The value of zero means using all the featurlinear_train_parcoordinate_paramCoordinateUpdate/__w/ml-builds/ml-builds/xgboost/src/linear/updater_shotgun.ccUnsupported feature selector for shotgun updater. Supported options are: {cyclic, shuffle}99R989Update linear model according to shotgun coordinate descent algorithm.N7xgboost6linear14ShotgunUpdaterE*N7xgboost6linearL40__make_LinearUpdaterReg_ShotgunUpdater__MUlvE_EWARNING: DEBUG: INFO: aucaucpr/__w/ml-builds/ml-builds/xgboost/src/metric/../common/common.hReceiver Operating Characteristic Area Under the Curve.Area under PR curve for both classification and rank.Invalid group with less than 3 samples is found on worker . Calculating AUC value requires at least 2 pairs of samples./__w/ml-builds/ml-builds/xgboost/src/metric/auc.cclabels.Size() == predts.size()labels.Size() != 0/__w/ml-builds/ml-builds/xgboost/src/metric/../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/metric/../common/threading_utils.hinfo.group_ptr_.size() >= 2/__w/ml-builds/ml-builds/xgboost/src/metric/auc.hPR-AUC supports only binary relevance for learning to rank./__w/ml-builds/ml-builds/xgboost/src/metric/../collective/aggregator.h/__w/ml-builds/ml-builds/xgboost/src/metric/../collective/allreduce.hn_classes != 0AUC doesn't support multi-target model./__w/ml-builds/ml-builds/xgboost/src/metric/../common/algorithm.hauc <= 1.0 + kRtEpsinfo.weights_.Size() == info.group_ptr_.size() - 1info.group_ptr_.back() == info.labels.Size()Dataset is empty, or contains only positive or negative samples.Total AUC across groups: , valid groups: N7xgboost6MetricEN7xgboost13MetricNoCacheEN7xgboost6metric7EvalAUCINS0_10EvalROCAUCEEEN7xgboost6metric10EvalROCAUCEN7xgboost6metric7EvalAUCINS0_9EvalPRAUCEEEN7xgboost6metric9EvalPRAUCEN7xgboost6metric26__make_MetricReg_EvalAUC__MUlPKcE_EN7xgboost6metric24__make_MetricReg_AUCPR__MUlPKcE_E/src/metric/auc.?????zo ?mphequantilegamma-nloglikgamma-deviancepoisson-nloglikmapemaermslermseMean 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./__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)tweedie-nloglik@%fsscanf(param, "%f", &threshold_) == 1unable to parse the threshold value for the error metricpreds.Size() == info.labels.Size()label and prediction size not match, hint: use merror or mlogloss for multi-class classificationinfo.labels.Shape(1) != 0info.labels.Shape(0) == info.num_row_slope for pseudo huber cannot be 0.slope != 0.0Check failed: !alpha_.Empty()dat[1] > 0n_targets != 0/__w/ml-builds/ml-builds/xgboost/src/metric/../common/quantile_loss_utils.hCheck failed: GetInitialised()Check failed: !quantile_alpha.Get().empty()quantile alpha must be in the range [0.0, 1.0].quantile_loss_paramname == "quantile"Rooted mean square error.Rooted mean square log error.Mean absolute error.Mean Pseudo-huber error.Binary classification error.tweedie-nloglikQuantile regression error.N7xgboost6metric15PseudoErrorLossEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowRMSEEEEN7xgboost6metric13EvalEWiseBaseINS0_12EvalRowRMSLEEEEN7xgboost6metric13EvalEWiseBaseINS0_10EvalRowMAEEEEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowMAPEEEEN7xgboost6metric13EvalEWiseBaseINS0_14EvalRowLogLossEEEN7xgboost6metric13EvalEWiseBaseINS0_20EvalPoissonNegLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_17EvalGammaDevianceEEEN7xgboost6metric13EvalEWiseBaseINS0_16EvalGammaNLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_9EvalErrorEEEN7xgboost6metric13EvalEWiseBaseINS0_18EvalTweedieNLogLikEEEN7xgboost6metric13QuantileErrorEN7xgboost6metric23__make_MetricReg_RMSE__MUlPKcE_EN7xgboost6metric24__make_MetricReg_RMSLE__MUlPKcE_EN7xgboost6metric22__make_MetricReg_MAE__MUlPKcE_EN7xgboost6metric23__make_MetricReg_MAPE__MUlPKcE_EN7xgboost6metric26__make_MetricReg_LogLoss__MUlPKcE_EN7xgboost6metric34__make_MetricReg_PseudoErrorLoss__MUlPKcE_EN7xgboost6metric35__make_MetricReg_PossionNegLoglik__MUlPKcE_EN7xgboost6metric32__make_MetricReg_GammaDeviance__MUlPKcE_EN7xgboost6metric31__make_MetricReg_GammaNLogLik__MUlPKcE_EN7xgboost6metric24__make_MetricReg_Error__MUlPKcE_EN7xgboost6metric33__make_MetricReg_TweedieNLogLik__MUlPKcE_EN7xgboost6metric32__make_MetricReg_QuantileError__MUlPKcE_E$$tI$t@quantile_loss_papseudo_huber_parư>/__w/ml-builds/ml-builds/xgboost/src/metric/metric.ccUnknown metric function merrormlogloss/__w/ml-builds/ml-builds/xgboost/src/metric/multiclass_metric.cuCheck failed: preds.Size() % info.labels.Size() == 0label and prediction size not matchmlogloss and merror are only used for multi-class classification, use logloss for binary classificationCheck failed: label_error >= 0 && label_error < static_cast(n_class)MultiClassEvaluation: label must be in [0, num_class),preds.Size() == 0nclass >= 1U num_class= but found in labelMulticlass classification error.Multiclass negative loglikelihood.N7xgboost6metric14EvalMClassBaseINS0_14EvalMatchErrorEEEN7xgboost6metric14EvalMatchErrorEN7xgboost6metric14EvalMClassBaseINS0_16EvalMultiLogLossEEEN7xgboost6metric16EvalMultiLogLossEN7xgboost6metric29__make_MetricReg_MatchError__MUlPKcE_EN7xgboost6metric31__make_MetricReg_MultiLogLoss__MUlPKcE_E]Bcox-nloglikInvalid output score, might be caused by invalid query group weight.Negative log partial likelihood of Cox proportional hazards model./__w/ml-builds/ml-builds/xgboost/src/metric/rank_metric.ccCheck failed: !collective::IsDistributed()Cox metric does not support distributed evaluationAMS must be in format ams@kams@/__w/ml-builds/ml-builds/xgboost/src/metric/../common/ranking_utils.hCheck failed: param_.GetInitialised()Groups() == info.weights_.Size()the size of label.score <= 1.0 + kRtEpsAMS metric for higgs.preprecision@k for rank.map@k for ranking.ndcg@k for ranking.weight.weights.size() == p_cache->Groups()metric AMS do not support distributed evaluationbest-ams-ratio=)|'02.lambdarank_paramCheck failed: p_cache->Param() == param_St23_Sp_counted_ptr_inplaceIN7xgboost3ltr8MAPCacheESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost3ltr9NDCGCacheESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost3ltr8PreCacheESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEN7xgboost6metric7EvalAMSEN7xgboost6metric7EvalCoxEN7xgboost6metric17EvalRankWithCacheINS_3ltr8PreCacheEEEN7xgboost6metric13EvalPrecisionEN7xgboost6metric17EvalRankWithCacheINS_3ltr9NDCGCacheEEEN7xgboost6metric8EvalNDCGEN7xgboost6metric17EvalRankWithCacheINS_3ltr8MAPCacheEEEN7xgboost6metric12EvalMAPScoreEN7xgboost6metric22__make_MetricReg_AMS__MUlPKcE_EN7xgboost6metric22__make_MetricReg_Cox__MUlPKcE_EN7xgboost6metric28__make_MetricReg_Precision__MUlPKcE_EN7xgboost6metric26__make_MetricReg_EvalMAP__MUlPKcE_EN7xgboost6metric27__make_MetricReg_EvalNDCG__MUlPKcE_Elambdarank_paramA@@aft-nloglikinterval-regression-accuracyNegative log likelihood of Accelerated Failure Time model./__w/ml-builds/ml-builds/xgboost/src/metric/survival_metric.cuAFT metric must be configured first, with distribution type and scaleCheck failed: metric_Unknown probability distributionndata == labels_upper_bound.Size()preds.Size() == info.labels_lower_bound_.Size()preds.Size() == info.labels_upper_bound_.Size()N7xgboost6metric20AFTNLogLikDispatcherEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common18NormalDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common20LogisticDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_14EvalAFTNLogLikINS_6common19ExtremeDistributionEEEEEN7xgboost6metric21EvalEWiseSurvivalBaseINS0_30EvalIntervalRegressionAccuracyEEEN7xgboost6metric29__make_MetricReg_AFTNLogLik__MUlPKcE_EN7xgboost6metric45__make_MetricReg_IntervalRegressionAccuracy__MUlPKcE_E-q=' @;f?/__w/ml-builds/ml-builds/xgboost/src/objective/../collective/../data/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/objective/adaptive.ccbegin_pos <= sorted_pos.size()Check failed: !position.empty()h_node_ptr.back() <= info.num_row_/__w/ml-builds/ml-builds/xgboost/src/objective/../common/threading_utils.h/__w/ml-builds/ml-builds/xgboost/src/objective/../collective/aggregator.h/__w/ml-builds/ml-builds/xgboost/src/objective/../common/stats.hCheck failed: h_row_set.empty()/__w/ml-builds/ml-builds/xgboost/src/objective/../collective/allreduce.h/__w/ml-builds/ml-builds/xgboost/src/objective/adaptive.hCheck failed: quantiles.empty() || quantiles.size() == n_leafCheck failed: tree[nidx].IsLeaf()/__w/ml-builds/ml-builds/xgboost/src/objective/../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/objective/../common/algorithm.hnptr.size() > 0n_unique == n_leafk + 1 < h_node_ptr.size()y_idx <= info.labels.Shape(1)hfAft"M"f[h@O O`a]T/__w/ml-builds/ml-builds/xgboost/src/objective/../common/transform.hNot part of device code. WITH_CUDA: /__w/ml-builds/ml-builds/xgboost/src/objective/aft_obj.cuinfo.labels_lower_bound_.Size() == ndatainfo.labels_upper_bound_.Size() == ndataNumber of weights should be equal to number of data points.info.weights_.Size() == ndataUnrecognized distributionsurvival:aftAFT loss functionN7xgboost3obj6AFTObjE*N7xgboost3objL30__make_ObjFunctionReg_AFTObj__MUlvE_E..@ؗҜ<@@pAp/__w/ml-builds/ml-builds/xgboost/src/objective/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/objective/init_estimation.hinfo.weights_.Size() == info.num_row_/__w/ml-builds/ml-builds/xgboost/src/objective/hinge.cuinfo.labels.Size() == preds.Size()Invalid shape of labels.binary:hingeHinge loss. Expects labels to be in [0,1f]N7xgboost3obj8HingeObjE*N7xgboost3objL32__make_ObjFunctionReg_HingeObj__MUlvE_EN7xgboost3obj12FitInterceptE/__w/ml-builds/ml-builds/xgboost/src/objective/lambdarank_obj.cch_n_rel.size() == label.Size()LambdaRank with NDCG loss as objectiveLambdaRank with RankNet loss as objectiveLambdaRank with MAP loss as objective./__w/ml-builds/ml-builds/xgboost/src/objective/../common/ranking_utils.hUnreachable.h_n_rel.size() == gptr.back()rank:ndcgrank:pairwiserank:mapinfo.labels.Shape(1) <= 1multi-output for LTR is not yet supported.info.labels.Shape(1) == 1multi-target for learning to rank is not yet supported./__w/ml-builds/ml-builds/xgboost/src/objective/lambdarank_obj.hg_rank.size() == g_label.Size()==UBML*6<810H5@`>JP}}L$#;)4tR^dinfo.labels.Size() == predt.Size()The size of label doesn't match the size of prediction.iter == 0ti+tj-St23_Sp_counted_ptr_inplaceIN7xgboost3ltr12RankingCacheESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEN7xgboost3obj13LambdaRankObjINS0_14LambdaRankNDCGENS_3ltr9NDCGCacheEEEN7xgboost3obj14LambdaRankNDCGEN7xgboost3obj13LambdaRankObjINS0_13LambdaRankMAPENS_3ltr8MAPCacheEEEN7xgboost3obj13LambdaRankMAPEN7xgboost3obj13LambdaRankObjINS0_18LambdaRankPairwiseENS_3ltr12RankingCacheEEEN7xgboost3obj18LambdaRankPairwiseE*N7xgboost3objL38__make_ObjFunctionReg_LambdaRankNDCG__MUlvE_E*N7xgboost3objL42__make_ObjFunctionReg_LambdaRankPairwise__MUlvE_E*N7xgboost3objL37__make_ObjFunctionReg_LambdaRankMAP__MUlvE_E^7{Gz?f%ffffBSoftmax for multi-class classification, output class index.Softmax for multi-class classification, output probability distribution./__w/ml-builds/ml-builds/xgboost/src/objective/multiclass_obj.cuCheck failed: preds.Size() == (static_cast(param_.num_class) * info.labels.Size())SoftmaxMultiClassObj: label size and pred size does not match. SoftmaxMultiClassObj: label must be in [0, num_class).label.Size() * num_class: preds.Size(): N7xgboost3obj20SoftmaxMultiClassObjE*N7xgboost3objL41__make_ObjFunctionReg_SoftmaxMultiClass__MUlvE_E*N7xgboost3objL42__make_ObjFunctionReg_SoftprobMultiClass__MUlvE_EҜ= n_alphas/__w/ml-builds/ml-builds/xgboost/src/objective/../common/quantile_loss_utils.hget(in["name"]) == Name()h_weights.size() == h_labels.Size()tMLM$fNR|^ 5!(.N7xgboost3obj18QuantileRegressionE*N7xgboost3objL42__make_ObjFunctionReg_QuantileRegression__MUlvE_E/__w/ml-builds/ml-builds/xgboost/src/objective/regression_obj.cureg:linear is now deprecated in favor of reg:squarederror.Scale the weight of positive examples by this factorMaximum delta step we allow each weight estimation to be. This parameter is required for possion regression.Tweedie variance power. Must be between in range [1, 2).Regression with squared error.Regression with root mean squared logarithmic error.Logistic regression for probability regression task.Logistic regression for binary classification task.Logistic regression for classification, output score before logistic transformation.Gamma regression using the gamma deviance loss with log link.Regression Pseudo Huber error.Poisson regression for count data.Cox regression for censored survival data (negative labels are considered censored).Tweedie regression for insurance data./__w/ml-builds/ml-builds/xgboost/src/objective/./regression_loss.hCheck failed: base_score > 0.0f && base_score < 1.0fbase_score must be in (0,1) for logistic loss, got: survival:coxreg:absoluteerrorinfo.labels.Size() != 0Ulabel set cannot be emptylabels are not correctly providedCheck failed: last_abs_y <= abs_yCoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed!StringView{get(in["name"])} == StringView{"reg:absoluteerror"}base_margin->Size() == 1Sum of weights is close to 0.0, skipping base score estimation.RegLossParamscale_pos_weightPoissonRegressionParamTweedieRegressionParamtweedie_variance_powerreg:squaredlogerrorreg:logisticbinary:logisticbinary:logitrawreg:gammareg:linearMean absoluate error.pseudo_huber_paramreg:pseudohubererrorreg:tweedietweedie_regression_parampoisson_regression_paramPoissonRegression: label must be nonnegativeTweedieRegression: label must be nonnegativereg_loss_paramlabel must be positive for gamma regression.label must be in [0,1] for logistic regressionlabel must be greater than -1 for rmsle so that log(label + 1) can be valid.N7xgboost3obj10RegLossObjINS0_16LinearSquareLossEEEN7xgboost3obj10RegLossObjINS0_15SquaredLogErrorEEEN7xgboost3obj10RegLossObjINS0_18LogisticRegressionEEEN7xgboost3obj10RegLossObjINS0_22LogisticClassificationEEEN7xgboost3obj10RegLossObjINS0_11LogisticRawEEEN7xgboost3obj10RegLossObjINS0_13GammaDevianceEEEN7xgboost3obj21PseudoHuberRegressionEN7xgboost3obj17PoissonRegressionEN7xgboost3obj13CoxRegressionEN7xgboost3obj17TweedieRegressionEN7xgboost3obj17MeanAbsoluteErrorE*N7xgboost3objL45__make_ObjFunctionReg_SquaredLossRegression__MUlvE_E*N7xgboost3objL38__make_ObjFunctionReg_SquareLogError__MUlvE_E*N7xgboost3objL42__make_ObjFunctionReg_LogisticRegression__MUlvE_E*N7xgboost3objL46__make_ObjFunctionReg_LogisticClassification__MUlvE_E*N7xgboost3objL35__make_ObjFunctionReg_LogisticRaw__MUlvE_E*N7xgboost3objL39__make_ObjFunctionReg_GammaRegression__MUlvE_E*N7xgboost3objL40__make_ObjFunctionReg_LinearRegression__MUlvE_E*N7xgboost3objL45__make_ObjFunctionReg_PseudoHuberRegression__MUlvE_E*N7xgboost3objL41__make_ObjFunctionReg_PoissonRegression__MUlvE_E*N7xgboost3objL37__make_ObjFunctionReg_CoxRegression__MUlvE_E*N7xgboost3objL41__make_ObjFunctionReg_TweedieRegression__MUlvE_E*N7xgboost3objL41__make_ObjFunctionReg_MeanAbsoluteError__MUlvE_Eư>pp0Я` `hD/__w/ml-builds/ml-builds/xgboost/src/predictor/../collective/allreduce.h/__w/ml-builds/ml-builds/xgboost/src/predictor/../data/proxy_dmatrix.h`@(PP`@ ``@p@``0 @ @ 0   h @ h H `8/__w/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.ccbase_margin.Shape(1) == ngroup/__w/ml-builds/ml-builds/xgboost/include/xgboost/tree_model.h/__w/ml-builds/ml-builds/xgboost/include/xgboost/multi_target_tree_model.hCheck failed: IsMultiTarget()Check failed: IsLeaf(nidx)Make predictions using CPU.Check failed: !model.learner_model_param->IsVectorLeaf()Predict interaction contributionCheck failed: !p_fmat->Info().IsColumnSplit()Predict interaction contribution support for column-wise data split is not yet implemented.Check failed: xgboost::collective::IsDistributed()column-split prediction is only supported for distributed trainingout_preds->size() == p_fmat->Info().num_row_ * (tree_end_ - tree_begin_)/__w/ml-builds/ml-builds/xgboost/src/predictor/../common/threading_utils.hout_preds->size() == p_fmat->Info().num_row_ * model_.learner_model_param->num_output_groupPredict contributionngroup != 0ncolumns != 0Predict contribution support for column-wise data split is not yet implemented.predict instancePredict instance with column splitPredict leaf with column splitm->NumColumns() == model.learner_model_param->num_featureNumber of columns in data must equal to trained model.Check failed: !p_m->Info().IsColumnSplit()Inplace predict support for column-wise data split is not yet implemented.Predict DMatrix with column splitout_preds->size() == n_samples * n_groupsSt19__shared_ptr_accessIN7xgboost4data10CSRAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt19__shared_ptr_accessIN7xgboost4data12DenseAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt12__shared_ptrIN7xgboost4data12DenseAdapterELN9__gnu_cxx12_Lock_policyE2EESt12__shared_ptrIN7xgboost4data10CSRAdapterELN9__gnu_cxx12_Lock_policyE2EEN7xgboost9predictor12CPUPredictorESt10shared_ptrIN7xgboost4data12DenseAdapterEESt10shared_ptrIN7xgboost4data10CSRAdapterEE*N7xgboost9predictorL34__make_PredictorReg_CPUPredictor__MUlPKNS_7ContextEE_E?/__w/ml-builds/ml-builds/xgboost/src/predictor/cpu_treeshap.ccunique_path[i].pweight == 0Unique path must have zero weightUnknown predictor type /__w/ml-builds/ml-builds/xgboost/src/predictor/predictor.ccmodel.learner_model_param->num_output_group != 0Invalid shape of base_margin. Expected: (margin.Shape(0) == n_samplesmargin.Shape(1) == n_groupsN7xgboost9PredictorE/__w/ml-builds/ml-builds/xgboost/src/tree/constraints.ccFailed to parse feature interaction constraint: newsize != 0With error: _/__w/ml-builds/ml-builds/xgboost/src/tree/../collective/allreduce.h/__w/ml-builds/ml-builds/xgboost/src/tree/fit_stump.cc/__w/ml-builds/ml-builds/xgboost/src/tree/../common/threading_utils.hCheck failed: h_sum.CContiguous()/__w/ml-builds/ml-builds/xgboost/src/tree/../common/common.hn_targets == gpair.Shape(1)ư>ư>/__w/ml-builds/ml-builds/xgboost/src/tree/hist/histogram.ccnodes_to_build.size() == valid_candidates.size()/__w/ml-builds/ml-builds/xgboost/src/tree/hist/../../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/tree/hist/param.ccCheck failed: *local_tree == ref_treedebug_synchronizCheck if all distributed tree are identical after tree constructmax_cached_hist_long (non-negatiMaximum number of nodes in CPU histogram cache. Only for internaHistMakerTrainPa/__w/ml-builds/ml-builds/xgboost/src/tree/multi_target_tree_model.ccCheck failed: this->IsLeaf(nidx)Collapsing a split node to leaf weight.Size() == this->NumTarget()weights_.size() >= next_nidx * weight.Size()parent_.size() == left_.size()split_idx < this->param_->num_featureparent_[nidx] != InvalidNodeId()p_weight.Size() == base_weight.Size()l_weight.Size() == left_weight.Size()r_weight.Size() == right_weight.Size()in_weight.Size() == weight_out.size()param_->size_leaf_vector > 1parent_.size() >= 1left_.size() == right_.size()nidx < left_.size()nidx < right_.size()nidx < parent_.size()nidx < split_index_.size()loss_changessum_hessianbase_weightssplit_indicessplit_conditionsdefault_leftparentsleft_childrenright_childrenN7xgboost15MultiTargetTreeE/__w/ml-builds/ml-builds/xgboost/src/tree/param.ccFound floating point number in interaction constraintsUnknown value type for interaction constraint:std::floor(d) == d/__w/ml-builds/ml-builds/xgboost/src/tree/tree_model.ccparam_.num_nodes == static_cast(nodes_.size())param_.num_nodes == static_cast(stats_.size())param_.deprecated_num_roots == 1Check failed: !IsMultiTarget()Please use JSON/UBJSON for saving models with multi-target trees.Check failed: !HasCategoricalSplit()Please use JSON/UBJSON for saving models with categorical splits.fmap.Size() <= std::numeric_limits::max()split_index < this->param_.num_featureCheck failed: this->p_mt_tree_fi->Read(¶m_, sizeof(TreeParam)) == sizeof(TreeParam)fi->Read(dmlc::BeginPtr(nodes_), sizeof(Node) * nodes_.size()) == sizeof(Node) * nodes_.size()fi->Read(dmlc::BeginPtr(stats_), sizeof(RTreeNodeStat) * stats_.size()) == sizeof(RTreeNodeStat) * stats_.size()static_cast(deleted_nodes_.size()) == param_.num_deletedthis->split_types_.size() == this->Size()this->GetSplitCategoriesPtr().size() == this->Size()get(out["tree_param"]["num_nodes"]) == std::to_string(param_.num_nodes)this->split_types_.size() == param_.num_nodesstatic_cast(deleted_nodes_.size()) == param_.num_deletedthis->split_categories_segments_.size() == param_.num_nodesDump text representation of treeDump json representation of treeDump graphviz representation of tree{param_.num_nodes != 0mean_values->size() > 0UCheck failed: node.IsLeaf()param_.size_leaf_vector > 1split_typecategories_segmentscategories_sizescategories_nodesUnknown Model Builder:dot tree dump GraphvizParamTreeParamtree_param Line , around ^`/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/json.h, Expect '"' but reach end of line ch == '\"'Error at, Expect '"' but get 'unknown string escape \ch == ','ch == ':', Expect ':' but get ', JSON object expect '}' or ',' 'Check failed: is_numerical in feature map is categorical but tree node is numerical.pos != std::string::nposCheck failed: is_categoricalUnknown feature map type. in feature map is numerical but tree node is categorical.܂܂Dparam_.num_nodes < std::numeric_limits::max()number of nodes in the tree exceed 2^31ch == '{', Expect '{' but get 'j_end - j_begin > 0std::numeric_limits::min() != max_catn_nodes != 0sum_hessian.size() == n_nodeslefts.size() == n_nodesrights.size() == n_nodesparents.size() == n_nodesindices.size() == n_nodesconds.size() == n_nodesloss_changes.size() == n_nodesbase_weights.size() == n_nodesdefault_left.size() == n_nodesyes_color#0000FFno_color#FF0000rankdircondition_node_paramsleaf_node_paramsLeaf node configurationgraph_attrsEdge color when meets the node condition.Edge color when doesn't meet the node condition.Passed to graphiz via graph_attr.Conditional node configurationAny other extra attributes for graphviz `graph_attr`.num_nodesnum_deletedsize_leaf_vectorNumber of features used in tree construction.Size of leaf vector, reserved for vector treelearning_ratemin_split_lossmax_depthmax_leavesgrow_policydepthwiselossguidemax_cat_to_onehotmax_cat_thresholdmin_child_weightreg_lambdareg_alphasubsamplesampling_methodgradient_basedcolsample_bynodecolsample_bylevelcolsample_bytreesketch_ratiocache_optrefresh_leafmonotone_constraintsinteraction_constraintssparse_thresholdetaLearning rate(step size) of update.Minimum loss reduction required to make a further partition.Maximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policyMaximum number of leaves; 0 indicates no limit.if using histogram-based algorithm, maximum number of bins per featureTree growing policy. 0: favor splitting at nodes closest to the node, i.e. grow depth-wise. 1: favor splitting at nodes with highest loss change. (cf. LightGBM)Maximum number of categories to use one-hot encoding based split.Maximum number of categories considered for split. Used only by partition-basedsplits.Minimum sum of instance weight(hessian) needed in a child.L2 regularization on leaf weightL1 regularization on leaf weightMaximum delta step we allow each tree's weight estimate to be. If the value is set to 0, it means there is no constraintRow subsample ratio of training instance.Sampling method. 0: select random training instances uniformly. 1: select random training instances with higher probability when the gradient and hessian are larger. (cf. CatBoost)Subsample ratio of columns, resample on each node (split).Subsample ratio of columns, resample on each level.Subsample ratio of columns, resample on each tree construction.EXP Param: Sketch accuracy related parameter of approximate algorithm.EXP Param: Cache aware optimization.Whether the refresh updater needs to update leaf values.Constraint of variable monotonicityConstraints for interaction representing permitted interactions.The constraints must be specified in the form of a nest list,e.g. [[0, 1], [2, 3, 4]], where each inner list is a group ofindices of features that are allowed to interact with each other.See tutorial for more informationpercentage threshold for treating a feature as sparse{parent}{stat} {left} {right}{parent}{stat}{left},gain={loss_chg},cover={sum_hess}, "gain": {loss_chg}, "cover": {sum_hess}digraph { graph [ rankdir={rankdir} ] {graph_attrs} {nodes}}{rankdir}{newline}{indent}{nodes}{newline}{indent}{nid}:[{fname}] yes={yes},no={no}{nid}{fname}{yes}{no}{ "nodeid": {nid}, "leaf": {leaf} {stat}}, "cover": {sum_hess} {leaf}{sum_hess}, missingyesno{child}{color}{branch} {nid} -> {child} [label="{branch}" color="{color}"] {nid} [ label="{fname}:{cond}" {params}] {cond}{params}{tabs}{nid}:leaf={leaf}{stats},cover={cover}{tabs}{stats}{nodes} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "yes": {yes}, "no": {no}{depth}{{properties} {stat}, "children": [{left}, {right} {indent}]}{properties}{missing} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {left}, "no": {right}, "missing": {missing} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {right}, "no": {left}, "missing": {missing} {nid} [ label="leaf={leaf-value}" {params}] limit >= 2..., {leaf-value}{tabs}{nid}:[{fname}<{cond}] yes={left},no={right},missing={missing}{tabs}{nid}:[{fname}:{cond}] yes={right},no={left},missing={missing}{<} {nid} [ label="{fname}{<}{cond}" {params}] {parent} {left} {right}" edge graph [ {key}="{value}" ] The following parameters for graphviz are not recognized: Failed to parse graphviz parameters: N7xgboost7RegTreeEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryISt6vectorIiSaIiEEEES5_EEN4dmlc9parameter10FieldEntryISt6vectorIiSaIiEEEEN7xgboost13TreeGeneratorEN7xgboost13TextGeneratorEN7xgboost13JsonGeneratorEN7xgboost17GraphvizGeneratorE*N7xgboostL33__make_TreeGenReg_TextGenerator__MUlRKNS_10FeatureMapERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE_E*N7xgboostL33__make_TreeGenReg_JsonGenerator__MUlRKNS_10FeatureMapERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE_E*N7xgboostL37__make_TreeGenReg_GraphvizGenerator__MUlRKNS_10FeatureMapENSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEbE_E?Unknown tree updater /__w/ml-builds/ml-builds/xgboost/src/tree/tree_updater.cc/__w/ml-builds/ml-builds/xgboost/src/tree/common_row_partitioner.hupper_bound < static_cast(std::numeric_limits::max())Tree constructor that uses approximate histogram construction for each node./__w/ml-builds/ml-builds/xgboost/src/tree/../data/../common/io.h/__w/ml-builds/ml-builds/xgboost/src/tree/hist/evaluate_splits.hpartition > 0/__w/ml-builds/ml-builds/xgboost/src/tree/../common/hist_util.hid != kMax/__w/ml-builds/ml-builds/xgboost/src/tree/../common/row_set.helem_of_each_node_.size() == 0Ui < ranges_.size()i < first_dimension_.size()/__w/ml-builds/ml-builds/xgboost/src/tree/hist/sampler.hexponent <= modend > beginnid < nodes_/__w/ml-builds/ml-builds/xgboost/src/tree/../common/partition_builder.hCheck failed: tree.IsLeaf(node.node_id)ptr_offset <= row_set.Data()->size()begin < end/__w/ml-builds/ml-builds/xgboost/src/tree/hist/histogram.hCheck failed: !nodes_to_build.empty()n_left == 0n_right == 0n_left + n_right == e.Size()begin + n_left <= e.endbegin + n_left + n_right == e.endtid < nthreads_/__w/ml-builds/ml-builds/xgboost/src/tree/../collective/broadcast.h/__w/ml-builds/ml-builds/xgboost/src/tree/hist/../split_evaluator.hp.monotone_constraints.size() <= n_featuresThe size of monotone constraint should be less or equal to the number of features./__w/ml-builds/ml-builds/xgboost/src/tree/../data/../common/ref_resource_view.hnidx != kRootCheck failed: out.Contiguous()param.sampling_method == TrainParam::kUniformOnly uniform sampling is supported, gradient-based sampling is only support by GPU Hist.vector::_M_fill_insertcut_ptr[fidx] <= static_cast(std::numeric_limits::max())cut_ptr[fidx + 1] <= static_cast(std::numeric_limits::max())Check failed: out_preds.Device().IsCPU()part.Size() == n_nodesout_preds.Size() > 0UCheck failed: p_last_treeout_preds.Shape(1) == n_targetsUpdatePredictionCache/__w/ml-builds/ml-builds/xgboost/src/tree/updater_approx.ccout_preds.Size() == data->Info().num_row_p_tree->LeftChild(nidx) + 1 == p_tree->RightChild(nidx)nodes == targeted_hists.size()row_ptr_[nid] == kMaxCheck failed: gpair.Contiguous()current_size_ == new_size/__w/ml-builds/ml-builds/xgboost/src/tree/hist/hist_cache.hCheck failed: p_nodes_to_buildCheck failed: !this->hist_.HasExceeded()Check failed: p_nodes_to_subnodes_to_build.size() >= nodes_to_sub.size()nodes_to_sub.size() + nodes_to_build.size() == valid_candidates.size() * 2gpair.Shape(1) == p_tree->NumTargets()t_gpair.Shape(0) == p_fmat->Info().num_row_gpair.Shape(1) == n_targetsp_fmat->Info().num_row_ == gpair.Shape(0)target_builders_.size() == n_targetsCheck failed: dummy_sub.empty()loss_chgsindexsplit_valuecat_bitsis_catleft_sumright_sumall_serialized.size() >= local_entries.size()Check failed: !features.empty()InitRootdecision_storage_.size() == decision.NumValues()/__w/ml-builds/ml-builds/xgboost/src/tree/hist/../../common/transform.hInitDatan_targets >= 1n_total_bins == page.cut.TotalBins()base_rowid == gmat.base_rowidgidx > -1any_missing == trueBuildHistogramEvaluateSplitsLeafPartitionCheck failed: hist_param_.GetInitialised()/__w/ml-builds/ml-builds/xgboost/src/tree/../collective/../data/../common/common.hFbRKN7xgboost4tree14CPUExpandEntryES3_EN7xgboost11TreeUpdaterEN7xgboost4tree19GlobalApproxUpdaterE*N7xgboost4treeL39__make_TreeUpdaterReg_GlobalHistMaker__MUlPKNS_7ContextEPKNS_7ObjInfoEE_EPFbRKN7xgboost4tree14CPUExpandEntryES3_EN7xgboost6common6ColumnIhEEN7xgboost6common16SparseColumnIterIhEESt23_Sp_counted_ptr_inplaceIN7xgboost6common13ColumnSamplerESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEN7xgboost6common6ColumnItEEN7xgboost6common16SparseColumnIterItEEN7xgboost6common6ColumnIjEEN7xgboost6common16SparseColumnIterIjEESt15_Sp_counted_ptrIPN7xgboost6common16PartitionBuilderILm2048EE9BlockInfoELN9__gnu_cxx12_Lock_policyE2EEGlobalApproxUpdahist_train_paramctx_ridx < position_.size()ridx exceed bound ridx= pos=/__w/ml-builds/ml-builds/xgboost/src/tree/../common/../collective/broadcast.hCheck failed: param_.cache_optSupport for `cache_opt' is removed in 1.0.0fmat.Info().num_row_ == position_.size()param_.sampling_method == TrainParam::kUniformOnly uniform sampling is supported, gradient-based sampling is only support by GPU Hist./__w/ml-builds/ml-builds/xgboost/src/tree/../common/../collective/../data/../common/common.hparam_.max_depth > 0exact tree method doesn't support unlimited depth./__w/ml-builds/ml-builds/xgboost/src/tree/../common/transform.hUpdater `grow_colmaker` or `exact` tree method doesn't support distributed training.Updater `grow_colmaker` or `exact` tree method doesn't support external memory training.Updater `grow_colmaker` or `exact` tree methodcolumn sample by node is not yet supported by the exact tree method/__w/ml-builds/ml-builds/xgboost/src/tree/split_evaluator.hgpair->Shape(1) == 1N7xgboost4tree8ColMaker7BuilderEN7xgboost4tree8ColMakerE*N7xgboost4treeL32__make_TreeUpdaterReg_ColMaker__MUlPKNS_7ContextET_E_EEXP Param: speed optimization fodefault_directioDefault direction choice when encountering a miscolmaker_train_pPruner that prune the tree according to statistics./__w/ml-builds/ml-builds/xgboost/src/tree/updater_prune.ccCheck failed: !tree[pid].IsLeaf()nid >= 1tree pruning end, extra nodes, pruned nodes, max_depth=N7xgboost4tree10TreePrunerE*N7xgboost4treeL34__make_TreeUpdaterReg_TreePruner__MUlPKNS_7ContextEPKNS_7ObjInfoEE_E/src/tree/updateGrow tree using quantized histogram.Check failed: p_tree->IsMultiTarget()left_child > candidate.nidright_child > candidate.nidstats_.Shape(1) == n_targets/__w/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.ccout_preds.Size() == data->Info().num_row_ * p_last_tree_->NumTargets()Check failed: p_mtimpl_Check failed: p_impl_root_sum_tloc.Shape(1) == gpair.Shape(1)Check failed: root_sum.CContiguous()row_ptr.size() >= 2UpdatePositionUpdateTreep_tree->LeftChild(candidate.nid) > candidate.nidCheck failed: param->monotone_constraints.empty()monotone constraintMultiTargetHistBuilderHistUpdaterFbRKN7xgboost4tree16MultiExpandEntryES3_EN7xgboost4tree17QuantileHistMakerE*N7xgboost4treeL41__make_TreeUpdaterReg_QuantileHistMaker__MUlPKNS_7ContextEPKNS_7ObjInfoEE_EN7xgboost6common15DenseColumnIterIhLb1EEEPFbRKN7xgboost4tree16MultiExpandEntryES3_EN7xgboost6common15DenseColumnIterItLb1EEEN7xgboost6common15DenseColumnIterIjLb1EEEN7xgboost6common15DenseColumnIterIhLb0EEEN7xgboost6common15DenseColumnIterItLb0EEEN7xgboost6common15DenseColumnIterIjLb0EEErefresh/__w/ml-builds/ml-builds/xgboost/src/tree/updater_refresh.ccbatch.Size() < std::numeric_limits::max()Refresher that refreshes the weight and statistics according to data.N7xgboost4tree13TreeRefresherE*N7xgboost4treeL37__make_TreeUpdaterReg_TreeRefresher__MUlPKNS_7ContextET_E_E/__w/ml-builds/ml-builds/xgboost/src/tree/../common/io.hsyncSyncher that synchronize the tree in all distributed nodes.N7xgboost4tree11TreeSyncherE*N7xgboost4treeL35__make_TreeUpdaterReg_TreeSyncher__MUlPKNS_7ContextET_E_ELibSVMParserParamLibFMParserParamCSVParserParamCheck failed: TryLoadCache()failed to build cache file finish reading at /__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/threadediter.hCheck failed: out_data_ != NULLCalling Value at beginning or end?/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.hcannot call ParseNextNo thread/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././parameter.h.split.partname_cache.size() == 1Uname_args.size() == 1U/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/uri_spec.honly one `#` is allowed in file path for cachefile specification/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./././strtonum.hlibsvmUnknown data type /__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data.ccFile formatindexing_modeIf >0, treat all feature indices as 1-based. If =0, treat all feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.libfmIf >0, treat all field and feature indices as 1-based. If =0, treat all field and feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.csvFile format.label_columndelimiterweight_columnColumn index (0-based) that will put into label.Delimiter used in the csv file.Column index that will put into instance weights./__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./row_block.hlabel.size() + 1 == offset.size()Check failed: offset.back() == value.size() || value.size() == 0offset.back() == index.size()param_.format == "csv"/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/csv_parser.hCheck failed: param_.label_column != param_.weight_column || param_.label_column < 0Must have distinct columns for labels and instance weights/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/libfm_parser.hparam_.format == "libfm"/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.hparam_.format == "libsvm"Check failed: producer_sig_.load(std::memory_order_acquire) == kDestroyCheck failed: cell != 0L || produce_end_.load(std::memory_order_acquire)Check failed: producer_sig_.load(std::memory_order_acquire) != kDestroyCheck failed: fi->Read(&label)Check failed: fi->Read(&weight)Check failed: fi->Read(&field)Check failed: fi->Read(&index)Check failed: fi->Read(&value)Check failed: fi->Read(&max_field, sizeof(IndexType))Check failed: fi->Read(&max_index, sizeof(IndexType))Bad RowBlock formatCheck failed: fi->Read(&qid)MB read,finish reading at %g MB/sec/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/disk_row_iter.hCheck failed: !producer_sig_processed_.load(std::memory_order_acquire)Check failed: producer_sig_.load(std::memory_order_acquire) == kProduceMake sure you call BeforeFirst not inconcurrent with Next!Check failed: produce_end_.load(std::memory_order_acquire)Delimiter '' is not found in the line. Expected '' as the delimiter to separate fields.Check failed: out->label.size() == 0 || out->label.size() + 1 == out->offset.size()Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size()sign == trueCheck failed: out->field.size() == out->index.size()Check failed: out->label.size() + 1 == out->offset.size()qid:/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/data/././text_parser.hchunk.size != 0UNSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS4_17RowBlockContainerImlEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_EEEEEEN4dmlc12ScopedThreadEN4dmlc8DataIterINS_8RowBlockIjfEEEEN4dmlc12RowBlockIterIjfEEN4dmlc8DataIterINS_8RowBlockImfEEEEN4dmlc12RowBlockIterImfEEN4dmlc8DataIterINS_8RowBlockIjiEEEEN4dmlc12RowBlockIterIjiEEN4dmlc8DataIterINS_8RowBlockImiEEEEN4dmlc12RowBlockIterImiEEN4dmlc8DataIterINS_8RowBlockIjlEEEEN4dmlc12RowBlockIterIjlEEN4dmlc8DataIterINS_8RowBlockImlEEEEN4dmlc12RowBlockIterImlEEN4dmlc6ParserIjfEEN4dmlc6ParserImfEEN4dmlc6ParserIjiEEN4dmlc6ParserImiEEN4dmlc6ParserIjlEEN4dmlc6ParserImlEEN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEEN4dmlc4data11DiskRowIterIjfEEN4dmlc4data12BasicRowIterIjfEEN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEEN4dmlc4data11DiskRowIterImfEEN4dmlc4data12BasicRowIterImfEEN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEEN4dmlc4data11DiskRowIterIjiEEN4dmlc4data12BasicRowIterIjiEEN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEEN4dmlc4data11DiskRowIterImiEEN4dmlc4data12BasicRowIterImiEEN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEEN4dmlc4data11DiskRowIterIjlEEN4dmlc4data12BasicRowIterIjlEEN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEEN4dmlc4data11DiskRowIterImlEEN4dmlc4data12BasicRowIterImlEEN4dmlc4data10ParserImplIjfEEN4dmlc4data14TextParserBaseIjfEEN4dmlc4data12LibSVMParserIjfEEN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEEN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEEN4dmlc4data14ThreadedParserIjfEEN4dmlc4data10ParserImplImfEEN4dmlc4data14TextParserBaseImfEEN4dmlc4data12LibSVMParserImfEEN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEEN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEEN4dmlc4data14ThreadedParserImfEEN4dmlc4data11LibFMParserIjfEEN4dmlc4data11LibFMParserImfEEN4dmlc4data9CSVParserIjfEEN4dmlc4data9CSVParserImfEEN4dmlc4data10ParserImplIjiEEN4dmlc4data14TextParserBaseIjiEEN4dmlc4data9CSVParserIjiEEN4dmlc4data10ParserImplImiEEN4dmlc4data14TextParserBaseImiEEN4dmlc4data9CSVParserImiEEN4dmlc4data10ParserImplIjlEEN4dmlc4data14TextParserBaseIjlEEN4dmlc4data9CSVParserIjlEEN4dmlc4data10ParserImplImlEEN4dmlc4data14TextParserBaseImlEEN4dmlc4data9CSVParserImlEEZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlPPSt6vectorINS0_17RowBlockContainerIjfEESaIS8_EEE_ZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlvE0_ZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlPPSt6vectorINS0_17RowBlockContainerImfEESaIS8_EEE_ZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlvE0_ZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjfEEE_ZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImfEEE_ZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjiEEE_ZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImiEEE_ZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjlEEE_ZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImlEEE_ZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlvE0_NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterISt6vectorINS3_4data17RowBlockContainerIjfEESaIS8_EEE4InitESt8functionIFbPPSA_EESC_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterISt6vectorINS3_4data17RowBlockContainerImfEESaIS8_EEE4InitESt8functionIFbPPSA_EESC_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjfEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImfEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjiEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImiEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjlEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImlEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEE/__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 CachedInputSplitBeforeFirst is not supportedhdfs://viewfs://s3://http://https://azure://unknown filesystem protocol stdinCheck failed: fp_ != NULLCheck failed: part < nsplitindexed_recordiounknown input split type rb/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io.ccPlease compile with DMLC_USE_HDFS=1 to use hdfsPlease compile with DMLC_USE_S3=1 to use S3Please compile with DMLC_USE_AZURE=1 to use AzureSingleFileSplit: fail to open invalid input parameter for InputSplit::Createneed to pass index file to use IndexedRecordIOCheck failed: nread == sizeof(size) has invalid cache file formatCheck failed: fi_->Read(p->begin, size) == sizeCheck failed: this->InitCachedIter()Failed to initialize CachedIterFvvEN4dmlc10InputSplitEN4dmlc2io15SingleFileSplitEN4dmlc8DataIterINS_2io14InputSplitBase5ChunkEEEN4dmlc12ThreadedIterINS_2io14InputSplitBase5ChunkEEEN4dmlc2io16CachedInputSplitEN4dmlc2io18ThreadedInputSplitEZN4dmlc2io16CachedInputSplit15InitPreprocIterEvEUlPPNS0_14InputSplitBase5ChunkEE_PFvvEZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlPPNS0_14InputSplitBase5ChunkEE_ZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlvE0_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlPPNS2_5ChunkEE_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlvE0_NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_2io14InputSplitBase5ChunkEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEE /__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.ccCheck failed: begin != endN4dmlc2io12LineSplitterE/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/recordio_split.ccCheck failed: fi->Read(&lrec, sizeof(lrec)) != 0(reinterpret_cast(begin) & 3UL) == 0U(reinterpret_cast(end) & 3UL) == 0UCheck failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->end(reinterpret_cast(chunk->begin) & 3UL) == 0U(reinterpret_cast(chunk->end) & 3UL) == 0UCheck failed: chunk->begin <= chunk->endCheck failed: p[0] == RecordIOWriter::kMagicinvalid record io formatCheck failed: p >= pbegin + 2Invalid RecordIO FormatCheck failed: cflag == 1UN4dmlc2io16RecordIOSplitterE/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.ccIndexedRecordIOSplitter does not support multiple index filesexpanded_list.size() == 1ulN4dmlc2io23IndexedRecordIOSplitterE   t L $ /__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 bytesN4dmlc2io14InputSplitBaseEstdoutCheck failed: allow_null LocalFileSystem::Open "": LocalFileSystem.GetPathInfo: /__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/local_filesys.ccLocalFileSystem.GetPathInfo: detected symlink LocalFileSystem.ListDirectory Check failed: !std::fseek(fp_, static_cast(pos), SEEK_SET)Check failed: std::fwrite(ptr, 1, size, fp_) == sizeFileStream.Write incompleteN4dmlc2io15LocalFileSystemEN4dmlc2io10FileStreamElstat(path.c_str(), &sb) == 0Couldn't remove file ~TemporaryDirectory(): /__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/filesystem.hdmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes/__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/filesys.ccCheck failed: !IsSymlink(info.path.name)Symlink not supported in TemporaryDirectorySuccessfully deleted temporary directory Could not remove temporary directory 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BBBG Ltg/BBB B(A0A8G 8A0A(B BBBG LmBBB B(A0A8Gv 8A0A(B BBBG L`t/BBB B(A0A8G 8A0A(B BBBG Ld@z/BBB B(A0A8G 8A0A(B BBBG ,01uk_ BFGv ABH .q,N_ XBOB B(A0A8GUkGBk 8A0A(B BBBD X\XBOB B(A0A8GUkGBk 8A0A(B BBBD X܊BOB B(A0A8GUkGBk 8A0A(B BBBD XBOB B(A0A8GUkGBk 8A0A(B BBBD Xp$BOB B(A0A8GUkGBk 8A0A(B BBBD XBOB B(A0A8GUkGBk 8A0A(B BBBD X(,BOB B(A0A8GUkGBk 8A0A(B BBBD XBOB B(A0A8GUkGBk 8A0A(B BBBD X$BOB B(A0A8GUkGBk 8A0A(B BBBD X<ȱBOB B(A0A8GUkGBk 8A0A(B BBBD X\BOB B(A0A8GUkGBk 8A0A(B BBBD X༂BOB B(A0A8GUkGBk 8A0A(B BBBD XPd‚BOB B(A0A8GUkGBk 8A0A(B BBBD XǂBOB B(A0A8GUkGBk 8A0A(B BBBD X͂BOB B(A0A8GUkGBk 8A0A(B BBBD Xd ӂBOB B(A0A8GUkGBk 8A0A(B BBBD X؂BOB B(A0A8GUkGBk 8A0A(B BBBD XhނBOB B(A0A8GUkGBk 8A0A(B BBBD XxBOB B(A0A8GUkGBk 8A0A(B BBBD XpBOB B(A0A8GUkGBk 8A0A(B BBBD X0BOB B(A0A8GUkGBk 8A0A(B BBBD XhBOB B(A0A8GUkGBk 8A0A(B BBBD XBOB B(A0A8GUkGBk 8A0A(B BBBD XDPBOB B(A0A8GUkGBk 8A0A(B BBBD XBOB B(A0A8GUkGBk 8A0A(B BBBD Xh BOB B(A0A8GUkGBk 8A0A(B BBBD XX BOB B(A0A8GUkGBk 8A0A(B BBBD XBOB B(A0A8GUkGBk 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Lvq> PpX^ '> BBB B(I0A8G 8D0A(B BBBK P$h > BBB B(I0A8G 8D0A(B BBBK 4qE> BDA D  DABF @Ps> BBD D(JH (D ABBA @dt> BBD D(JH (D ABBA Lun> BBB B(A0D8GJ 8A0A(B BBBH L(@xQT> BBB B(A0D8GK 8A0A(B BBBG PxP{@> BBF B(D0A8Dv 8A0A(B BBBA LFV> BBB B(A0D8GJ 8A0A(B BBBH L̂B> BBB B(A0D8GJ 8A0A(B BBBH <lY.> BBA D(H` (D ABBA @$> BBD D(JH (D ABBA L= BBB B(A0D8GJ 8A0A(B BBBH @@= BBD D(JI (D ABBA L = BBB B(A0A8G 8A0A(B BBBH LF;> BBB B(A0D8GJ 8A0A(B BBBH L$'> BBB B(A0D8GJ 8A0A(B BBBH Lt> BEB B(A0A8D`] 8A0A(B BBBH P4=u6= BEB E(D0A8GW 8A0A(B BBBE q= t*lGBB L(D0D8GPF8A0A(B BBBJHPx 8A0A(B BBBF *8Ps= BBB B(D0D8F 8A0A(B BBBF L LQg= BBB B(A0D8GK 8A0A(B BBBG Pl \S= BBB B(D0A8G 8D0A(B BBBC 8 x?uD= AC DEED.0f.H K 9qh{= L != BBB B(A0D8GJ 8A0A(B BBBH x<,eUBB B(D0A8J@ 8A0A(B BBBCH@ 8A0A(B BBBE L!F= BBB B(A0D8GJ 8A0A(B BBBH L<"< BBB B(A0D8GJ 8A0A(B BBBH L"|< BBB B(A0D8GJ 8A0A(B BBBH L"< BBB B(A0D8GJ 8A0A(B BBBH 4-|„SDA DBFH Hd#$Ȅg< BBB D(A0D= 0D(A BBBI D#Ʉ5< BBB A(A0Dp 0A(A BBBD L#p̄< BBB E(A0A8Dp 8A0A(B BBBE HH$@>u; BBB D(D0G 0A(A BBBG $ q(; A8$@τ'< BBD D  DBBD D$Є< BBB A(A0Do 0A(A BBBE 80,ӄBED D(D0> (D ABBA Lx%؄; BBB E(A0A8Dp 8A0A(B BBBE H%ۄn; BBB B(D0G) 0D(B BBBA D&d݄E; BBB A(A0Dt 0A(A BBBH <\& ^'; BBA A(D@ (A ABBH th1,GBB L(D0D8GPF8A0A(B BBBJHPx 8A0A(B BBBF P'@uq: BBB E(D0D8G+ 8A0A(B BBBA h']q[c: P'Cu{: BBE E(D0A8G 8D0A(B BBBH '@qk: P(tFu: BEB E(D0D8D  8A0A(B BBBH X(Mqs: H3cH\38[BBB B(K0A8DP| 8A0A(B BBBB H3LJBBL B(A0A8D`o 8A0A(B BBBG P() Iu 9 BBE E(D0D8G 8A0A(B BBBG |)q: P)Ru+: BFB B(A0D8G{ 8A0A(B BBBC )ql : @*`o: BBD D(JI (D ABBA (5H<5HP54Hd5pHx5H5H5$H5`H5H5H5H88+Pg9 BBD D  DBBD Dt+D9 BBB A(A0Do 0A(A BBBE L+, 9 BBB B(A0D8GJ 8A0A(B BBBH L ,9 BBB E(A0A8Dp 8A0A(B BBBE @\, Xu8 AC BEH.0m.. m E f. ,q#9 8,_u0S9 AC FF. M.B G -Bq9 P$-tdu9 BBB E(A0D8G  8A0A(B BBBC x-q9 P-fu9 BBB E(A0D8G  8A0A(B BBBC -q9 P.hu9 BBE E(A0A8GC 8A0A(B BBBD h.1q9 @.: BBD D(Js (D ABBA 4.ju9 BBD Dp  DBBA /@q9 pH(/`lu9 BBB A(D0G 0A(A BBBD t/q9 P/p9 BBB B(A0D8D 8A0A(B BBBH H: PBBB B(A0A8NP 8A0A(B BBBF <809 BBA D(G`G (A ABBC Px0 9 BBB B(A0A8G 8A0A(B BBBH P09 BEB E(A0D8G 8A0A(B BBBD P 1mu9 BBE E(D0D8GB 8A0A(B BBBG t1qq9 d<puDDB PL1pu9 BBB B(D0D8J 8A0A(B BBBI 2qm9 D,2 vu9 BEE D(D0GpD 0A(A BBBI t2q9 pL2<9 BBB B(A0A8D` 8A0A(B BBBE P2 (9 BBB B(A0D8G 8A0A(B BBBJ t>|GBB L(D0D8GPF8A0A(B BBBJHPx 8A0A(B BBBF P3uu{9 BBB B(D0D8G~ 8A0A(B BBBA 4qW: H>PBBB B(A0A8NP 8A0A(B BBBF Px4Бu: BBB E(A0D8G 8A0A(B BBBA 4qw; \?BBB B(A0A8DP 8A0A(B BBBC |8F0A(B BBB`@hBFB E(A0D8DP_ 8G0A(B BBBI z 8G0A(B BBBF P5 : BBB B(A0A8G 8A0A(B BBBH P6@u<; BBB B(A0A8G 8A0A(B BBBI \6)q ; 8LA!LAA E ABJ W ABA L6,# : BBB B(A0A8G 8A0A(B BBBF P 7|,; BBB B(A0D8M 8A0A(B BBBG L`7(u  ; BBB B(A0A8G 8A0A(B BBBC 7q/; P7d4 ; BBB B(A0D8M 8A0A(B BBBH P(8=; BFA D(DPh (A ABBA ) (H ABBJ ,|8>: BFG0J ABD 88|u: AC FED=.X. A $8q^; A ,9>p< ADG u AAA P@9ua; BEB B(A0D8J 8A0A(B BBBF 9Yq; @9u; AC DEED.X..O.T A 9zq; 8 :ud; AC DJF.X.F A \:q; 8:u; AC FED7 F h.X. :0q < 4:ud'< BFJ N  AABB ;qq< <8; ul;< BGD J(N (A ABBE x;qr+< P;0uG< BBE E(D0D8Ga 8A0A(B BBBH ;qv+< D<u?< BBE E(D0G@i 0P(B BBBF X<q!< @P|<u:; BBB B(A0D8G> 8A0A(B BBBD <q; P<u; BBB E(D0A8G 8D0A(B BBBG H=q6; Pl=LuU; BBB E(D0A8J 8A0A(B BBBC =q; 8=4u  < AC BEEMW.O.r K >qC< PD>us< BBE E(D0D8J 8A0A(B BBBE >q"< P>Luz< BBB E(D0A8J 8A0A(B BBBF ?0q< P4?Tu5< BBB E(D0D8J$ 8A0A(B BBBE ?q< H?8= BBB D(D0G 0A(A BBBH H?0;< BBB D(D0G 0A(A BBBH HD@=< BBB D(D0G 0A(A BBBH H@8@< BBB D(D0G 0A(A BBBH H@Bk< BBB D(D0G 0A(A BBBH H(A@EB< BBB D(D0G 0A(A BBBH HtAG< BBB D(D0G 0A(A BBBH HAHJ; BBB D(D0G 0A(A BBBH H BL; BBB D(D0G 0A(A BBBH HXBPO; BBB D(D0G 0A(A BBBH HBQu; BBB D(D0G 0A(A BBBH PBuFL; BBB B(A0A8GM 8A0A(B BBBH DCqq; HhCS; BBB D(D0G 0A(A BBBH HCdV: BBB D(D0G 0A(A BBBH HDX: BBB D(D0G 0A(A BBBH HLDl[: BBB D(D0G 0A(A BBBH HD]k: BBB D(D0G 0A(A BBBH HDt`B: BBB D(D0G 0A(A BBBH H0Eb: BBB D(D0G 0A(A BBBH H|E|e9 BBB D(D0G 0A(A BBBH HEh9 BBB D(D0G 0A(A BBBH HFj9 BBB D(D0G 0A(A BBBH H`Fmu9 BBB D(D0G 0A(A BBBH PFlvFL9 BBB B(A0A8GM 8A0A(B BBBH Gqq9 H$Go9 BBB D(D0G 0A(A BBBH HpGq8 BBB D(D0G 0A(A BBBH HGt8 BBB D(D0G 0A(A BBBH HHv8 BBB D(D0G 0A(A BBBH HTH$yk8 BBB D(D0G 0A(A BBBH HH{B8 BBB D(D0G 0A(A BBBH HH,~8 BBB D(D0G 0A(A BBBH H8I7 BBB D(D0G 0A(A BBBH HI47 BBB D(D0G 0A(A BBBH HI7 BBB D(D0G 0A(A BBBH HJ<u7 BBB D(D0G 0A(A BBBH PhJ#vFL7 BBB B(A0A8GM 8A0A(B BBBH Jzqq7 HJH7 BBB D(D0G 0A(A BBBH H,Ǩ6 BBB D(D0G 0A(A BBBH LDV@@vZBBB B(A0A8G4 8A0A(B BBBA HKm6 BBB D(D0G 0A(A BBBH LVBvZBBB B(A0A8G4 8A0A(B BBBA HdL45 BBB D(D0G 0A(A BBBH HL5 BBB D(D0G 0A(A BBBH LW|CvZBBB B(A0A8G4 8A0A(B BBBA HLM악R5 BBB D(D0G 0A(A BBBH LdX@EvZBBB B(A0A8G4 8A0A(B BBBA HM 4 BBB D(D0G 0A(A BBBH H4N4 BBB D(D0G 0A(A BBBH HN(4 BBB D(D0G 0A(A BBBH HN^4 BBB D(D0G 0A(A BBBH LY FvZBBB B(A0A8G4 8A0A(B BBBA HhOࡅ3 BBB D(D0G 0A(A BBBH HOd3 BBB D(D0G 0A(A BBBH HP覅3 BBB D(D0G 0A(A BBBH HLPlj3 BBB D(D0G 0A(A BBBH HPA3 BBB D(D0G 0A(A BBBH HPt3 BBB D(D0G 0A(A BBBH H0Q2 BBB D(D0G 0A(A BBBH H|Q|2 BBB D(D0G 0A(A BBBH HQ2 BBB D(D0G 0A(A BBBH HRt2 BBB D(D0G 0A(A BBBH H`RK2 BBB D(D0G 0A(A BBBH HR"2 BBB D(D0G 0A(A BBBH PRDvF1 BBB B(A0A8GM 8A0A(B BBBH LS\qq1 HpS1 BBB D(D0G 0A(A BBBH L^,bvZBBB B(A0A8G4 8A0A(B BBBA H TC1 BBB D(D0G 0A(A BBBH HXTPą1 BBB D(D0G 0A(A BBBH HTƅ0 BBB D(D0G 0A(A BBBH L_XcvZBBB B(A0A8G4 8A0A(B BBBA H@UɅx0 BBB D(D0G 0A(A BBBH HU˅O0 BBB D(D0G 0A(A BBBH HU΅&0 BBB D(D0G 0A(A BBBH L`dvZBBB B(A0A8G4 8A0A(B BBBA HtVDЅ/ BBB D(D0G 0A(A BBBH LaHfvZBBB B(A0A8G4 8A0A(B BBBA HWx҅4/ BBB D(D0G 0A(A BBBH H\Wԅ / BBB D(D0G 0A(A BBBH HWׅ. BBB D(D0G 0A(A BBBH HWڅ. BBB D(D0G 0A(A BBBH H@X܅. BBB D(D0G 0A(A BBBH HX ߅g. BBB D(D0G 0A(A BBBH HX>. BBB D(D0G 0A(A BBBH H$Y. BBB D(D0G 0A(A BBBH HpY- BBB D(D0G 0A(A BBBH HY- BBB D(D0G 0A(A BBBH HZ- BBB D(D0G 0A(A BBBH HTZ$q- BBB D(D0G 0A(A BBBH HZH- BBB D(D0G 0A(A BBBH HZ,- BBB D(D0G 0A(A BBBH P8[0dvF, BBB B(A0A8GM 8A0A(B BBBH [qq, H[8, BBB D(D0G 0A(A BBBH H[, BBB D(D0G 0A(A BBBH HH\@g, BBB D(D0G 0A(A BBBH H\>, BBB D(D0G 0A(A BBBH H\H, BBB D(D0G 0A(A BBBH H,]+ BBB D(D0G 0A(A BBBH Hx]P+ BBB D(D0G 0A(A BBBH H]+ BBB D(D0G 0A(A BBBH H^X q+ BBB D(D0G 0A(A BBBH H\^ H+ BBB D(D0G 0A(A BBBH H^`+ BBB D(D0G 0A(A BBBH P^~vF* BBB B(A0A8GM 8A0A(B BBBH H_Dqq* Hl_l* BBB D(D0G 0A(A BBBH H_* BBB D(D0G 0A(A BBBH H`tg* BBB D(D0G 0A(A BBBH HP`>* BBB D(D0G 0A(A BBBH H`|* BBB D(D0G 0A(A BBBH H`) BBB D(D0G 0A(A BBBH H4a) BBB D(D0G 0A(A BBBH Ha") BBB D(D0G 0A(A BBBH Ha$q) BBB D(D0G 0A(A BBBH Hb'H) BBB D(D0G 0A(A BBBH Hdb)) BBB D(D0G 0A(A BBBH PbXvF( BBB B(A0A8GM 8A0A(B BBBH cqq( H(c+( BBB D(D0G 0A(A BBBH Htc$.( BBB D(D0G 0A(A BBBH Hc0g( BBB D(D0G 0A(A BBBH H d,3>( BBB D(D0G 0A(A BBBH HXd5( BBB D(D0G 0A(A BBBH LpovZBBB B(A0A8G4 8A0A(B BBBA Hd7' BBB D(D0G 0A(A BBBH H@eh:s' BBB D(D0G 0A(A BBBH LXp,vZBBB B(A0A8G4 8A0A(B BBBA He<& BBB D(D0G 0A(A BBBH LpvZBBB B(A0A8G4 8A0A(B BBBA Hxf>& BBB D(D0G 0A(A BBBH HfTAX& BBB D(D0G 0A(A BBBH HgC/& BBB D(D0G 0A(A BBBH L(rvZBBB B(A0A8G4 8A0A(B BBBA Hg F% BBB D(D0G 0A(A BBBH HgH% BBB D(D0G 0A(A BBBH HDhKd% BBB D(D0G 0A(A BBBH HhM;% BBB D(D0G 0A(A BBBH HhP% BBB D(D0G 0A(A BBBH H(iR$ BBB D(D0G 0A(A BBBH Hti$U$ BBB D(D0G 0A(A BBBH HiW$ BBB D(D0G 0A(A BBBH H j,Zn$ BBB D(D0G 0A(A BBBH HXj\E$ BBB D(D0G 0A(A BBBH Hj4_$ BBB D(D0G 0A(A BBBH PjvF# BBB B(A0A8GM 8A0A(B BBBH Dk,qq# Lhkv:# BBB B(A0A8G ] 8A0A(B BBBH k)q0#  4k w # AC DEED A C. lq$ 88lw$ AC DEEK[ H .X. tlxq$ Hdw`1BBB B(N0A8DP 8A0A(B BBBG Pl#w$ BEE B(E0A8G 8A0A(B BBBD 8mq2$ P\m`$ BBB B(A0D8M 8A0A(B BBBG Lmh$ LLB B(A0A8DP  8A0A(B BBBK Lnxl)$ BKB B(A0A8G`( 8A0A(B BBBA PPn((w$ BBB B(D0D8J 8A0A(B BBBE nyq$ LnsX$ BBO B(A0A8D`r 8A0A(B BBBI Pov$ BBB B(A0A8K 8A0A(B BBBB @lo}u$ AC FQe. G k.Z..PoX)w c$ BBB B(A0A8Gb 8A0A(B BBBC pq1$ zP&t.DW {ȃ! {xAf I ,<{ BDA t ABB l{肆xAf I {%t.DW{ { {{$!{ | |IIp G H<|q,P|qBAA D0 AAB(|GAG _IB4q# BDA DP  DABF |4,r܂" BBD D0i  DBBC driq" 0hr$o" BBB B(A0A8Gx 8A0A(B BBBE 7 8I0A(B BBBO 4}(IAE n ABP QAB@}BAA  ABP Q ABD AEBPls BBB B(A0A8D` 8A0A(B BBBK qc `L BBB B(A0A8D`@ 8A0A(B BBBH Xqc `L|< BBB B(A0A8D`@ 8A0A(B BBBH ̚qcT `Lx< BBB B(A0A8D`@ 8A0A(B BBBH @qc `Ld BBB B(A0A8D`@ 8A0A(B BBBH qc `L؛ BBB B(A0A8D`a 8A0A(B BBBG (qcR `LL: BBB B(A0A8D`b 8A0A(B BBBF qc `LH BBB B(A0A8D`k 8A0A(B BBBE qc `L4 BBB B(A0A8D`k 8A0A(B BBBE qcP `LÈ8 BBB B(A0A8D`k 8A0A(B BBBE wqc `L\ƈ BBB B(A0A8D`k 8A0A(B BBBE lfqc `LɈ BBB B(A0A8D` 8A0A(B BBBE UqcN `LD͈6 BBB B(A0A8D`4 8A0A(B BBBD TDqc `Lxpш BBB B(A0A8D` 8A0A(B BBBE ȟ3qc `L Ո BBB B(A0A8D` 8A0A(B BBBE <"qcL `L`؈4 BBB B(A0A8D` 8A0A(B BBBE qc `LԠD܈ BBB B(A0A8D` 8A0A(B BBBE $qc `LH߈r BBB B(A0A8D` 8A0A(B BBBE qcJ `Lr2 BBB B(A0A8D` 8A0A(B BBBE qc `L0^ BBB B(A0A8D` 8A0A(B BBBD qc `L^ BBB B(A0A8D` 8A0A(B BBBD qcH `L^0 BBB B(A0A8D` 8A0A(B BBBD hqc `L^ BBB B(A0A8D` 8A0A(B BBBD ܣqc `L BBB B(A0A8D` 8A0A(B BBBK PqcF `Lt4. BBB B(A0A8D` 8A0A(B BBBK Ĥxqc `L BBB B(A0A8D`@ 8A0A(B BBBH 8gqc `L\ BBB B(A0A8D`@ 8A0A(B BBBH VqcD `LХ8, BBB B(A0A8D`@ 8A0A(B BBBH Eqc `LDt BBB B(A0A8D`@ 8A0A(B BBBH 4qc `L BBB B(A0A8D` 8A0A(B BBBG #qcB `L,\ * BBB B(A0A8D`L 8A0A(B BBBD |qc `L BBB B(A0A8D`k 8A0A(B BBBE qc `L~ BBB B(A0A8D`k 8A0A(B BBBE dqc@ `L`( BBB B(A0A8D`k 8A0A(B BBBE بqc `L BBB B(A0A8D`k 8A0A(B BBBE Lqc `Lp| BBB B(A0A8D` 8A0A(B BBBA qc> `L& BBB B(A0A8D` 8A0A(B BBBA 4qc `LX0# BBB B(A0A8D` 8A0A(B BBBE qc `L̪&z BBB B(A0A8D` 8A0A(B BBBE qc< `L@h*$ BBB B(A0A8D` 8A0A(B BBBE yqc `L. BBB B(A0A8D` 8A0A(B BBBE hqc `L(1x BBB B(A0A8D`^ 8A0A(B BBBJ xWqc: `L 8q" BBB B(A0A8D` 8A0A(B BBBB Fqc `L> BBB B(A0A8D`r 8A0A(B BBBF `5qc `Ld@wv BBB B(A0A8D`/ 8A0A(B BBBI ԭ$qc8 `LpAw  BBB B(A0A8D`- 8A0A(B BBBK Hqc `Ll|Bn BBB B(A0A8D` 8A0A(B BBBI qc `LxEnt BBB B(A0A8D` 8A0A(B BBBI 0qc6 `LTtHn BBB B(A0A8D` 8A0A(B BBBI qc `LȯpKz BBB B(A0A8D` 8A0A(B BBBE qc `L<|Nzr BBB B(A0A8D` 8A0A(B BBBE qc4 `LQz BBB B(A0A8D` 8A0A(B BBBE qc `P$T BBB B(A0A8G 8D0A(B BBBA xq (h~KAG dIBPȱZ" BBB B(D0D8G 8D0A(B BBBE qP 8@~: AF HK. D E. 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