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SH$H=H\$8L$|H=|H=|H|$I馝I᝸HL$HLt$8ٝI鏝I@I!HbL$HLT$8隝H驞H鷞H齝f.fAWAVIAUATUSH(Hw(HG0HWHHO LnHD$Lg8H$H_HL$Ht$L9vwM}IDI@MGPL9t MOPIq讚I MW0L9t M_0Is蔚I?IGH9IWI`HrsL9uIL9,$wH<$H9|$H;\$tbfDH{@LCPL9t LKPIq.H{ LS0L9t L[0IsH;HCH9tHSH`HrH9\$uL9d$tjDI|$@I\$PH9tIL$PHqÙI|$ It$0H9tMl$0Iu覙I<$M|$L9Il$I`Hu肙L9d$uI>HMfHI^(Ml$I9SIH;HIBMIAI9%MIItmItVIt?It(ItH;H옶H;HۘH;HʘH;H蹘H;H記H;H藘H;H膘I9vxH;H@pH{ȾbH{оTH{ؾFH{8H{*H{H{I9wI>IvH([]HA\A]A^A_뗶I`I9IL9,$dI`L9d$I>H6H([]A\A]A^A_fDH`H9\$9H;\$H{@LcPL9t HKPHqVH{ Hs0H9t Lk0IuD}PLeHB'HkHHMHfHnfHnHfHnflflK0[@HD$dH+%(HH([]A\A]A^A_@MNHL$DM@L(MerfLqK 6I9MҾHIEMl2I9J< LHs(L)IHL4HCHHPH9t H)LBILCH;J4>L;LkMA~M,.Ls(LkHIfInflCImHk8HHk@Ht$H} 1YLL$HE HLM0LLLl$HE Ht$1HYHT$HEHHULLLt$HMyHt$H}@1pYL\$HE@HL]PLLULd$H}@M)IILO4H)L9vL9LGL9H}H)LGH= sH=+JTH= sH= sH|$LIH4IH} I9t Hu0HvtH}H9|$t HuH\LH[HH{BIe`L-f.Hi Ht3UHSHW HHCHHuH]f.PXvector::_M_range_insertbasic_string::_M_construct null not valid/__w/ml-builds/ml-builds/xgboost/src/c_api/c_api.ccDMatrix/Booster has not been initialized or has already been disposed.` is deprecated, please use `XGBoosterSaveModelToBuffer` instead.XGBoost federated mode detected, not splitting data among workersXGBoost distributed mode detected, will split data among workersXGDMatrixSetGroup is deprecated, use `XGDMatrixSetUIntInfo` instead.Check failed: type >= 1 && type <= 4binary 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.htmlCurrent DMatrix type does not support set data./__w/ml-builds/ml-builds/xgboost/src/c_api/../common/common.hXGBoost version not compiled with GPU support.static_cast*>(handle) ->get() ->Info() .group_ptr_.size() == 0Uslice does not support group structureXGDeviceQuantileDMatrixCreateFromCallback is deprecated. Use `XGQuantileDMatrixCreateFromCallback` instead.p_m->Info().num_col_ <= std::numeric_limits::max()/__w/ml-builds/ml-builds/xgboost/include/xgboost/data.hCheck failed: impl_ != nullptr/__w/ml-builds/ml-builds/xgboost/src/c_api/../data/../common/threading_utils.hUnknown field for Booster feature info:Invalid thread limit for OpenMP.XGDMatrixCreateFromArrowCallbackCheck failed: !schema_->columns.empty()Cannot import record batch without a schemaDMatrix has not been initialized or has already been disposed.Check failed: iteration_end == 0Only one of the `ntree_limit` or `iteration_range` can be specified.`ntree_limit` is deprecated, use `iteration_range` instead.get(config["cache_id"]) == 0Invalid input type for inplace predict.FeatureMap feature index exceed boundfeatures.size() <= scores.size()scores.size() % features.size() == 0ulfeatures.size() == scores.size()get(array).size() == 1Check failed: ec == std::errc()%02d:%02d:%02d] basic_string::appendOnly dimensional array is valid.Invalid pointer argument: json_parametersbufXGBoosterGetModelRawout_dptrout_lenCheck failed: p_outfnameBit fieldBooleanIntegerUnsigned integerFloating pointComplex floating pointTimedeltaDatetimeObjectStringUnicodeOtherInvalid type code: in `typestr' of input array. Or open an issue.-Check failed: p_mCheck failed: mc_interface_strCheck failed: c_interfacename_strCheck failed: out_strjsonubjdtrainCheck failed: dtrgradhessout_indptrout_indicesout_dataCheck failed: page.pagen_threads >= 1feature_namefeature_typeout_resultCheck failed: _refInvalid handle to ref.limit >= 1nthreadmax_binnextresetnbatchXGBoosterSaveModelToBufferdeprecatedUnknown format: `XGDMatrixCreateFromCallbackcache_prefixout_featuresdmatsevnamesc_json_configXGBoosterPredictFromDMatrixiteration_beginiteration_endntree_limittrainingstrict_shapeout_dimout_shapeCache ID is not supported yetInplacePredictImplCheck failed: p_predtCheck failed: proxyarray_interfacestr.size() >= 3str[0] == '{'ftypetextfmapXGBoosterFeatureScoreimportance_typefeature_mapfeature_namestree_idxidx < names_.size()out_n_featuresout_scoresColumn: json_strUnknown global parameters: { Check failed: e/__w/ml-builds/ml-builds/xgboost/src/c_api/../data/adapter.hCannot reset RecordBatchesIterAdapterCheck failed: at_first_0,x+-x+x+x+.x+0.P.x+x+x+x+x+x+x+x+x+x+x+p..x+x+.x+x+.x+x+x+.x+x+x+x+x+x+/0/Cannot reset IteratorAdapter/__w/ml-builds/ml-builds/xgboost/src/c_api/../data/proxy_dmatrix.hSlicing DMatrix is not supported for Proxy DMatrix./__w/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/utils.hread can not have position excceed buffer lengthwrite position exceed fixed buffer sizevector::_M_default_append/__w/ml-builds/ml-builds/xgboost/src/c_api/c_api_utils.hIncorrect type for: ``, expecting: ``, got: ``. vs. ) chunksize == groupsUnknown prediction type:std::accumulate(shape.cbegin(), shape.cend(), static_cast(1), std::multiplies<>{}) == chunksize * rowsCheck failed: pp_mInvalid DMatrix handleNot implemented.vector::_M_realloc_insert/__w/ml-builds/ml-builds/xgboost/include/xgboost/json.hInvalid cast, from gblinearlearnergradient_boostergbtree_model_paramnum_parallel_treestoiUnknown booster:Argument `` is required for `Invalid missing value: Argument `missing` is required.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 interfacetypestrmaskEmpty data passed in.map::atj_shape.size() == 1type_length == 1stridesstrides.size() == 1Memory should be contiguous.vector::_M_range_check: __n (which is %zu) >= this->size() (which is %zu)basic_string::at: __n (which is %zu) >= this->size() (which is %zu)mask with bitfield type should be of 1 byte per bitfield.mask with integer type should be of 1 byte per integer.mask must be of integer type or bit field type.get(strides.at(0)) == type_length+sCheck failed: columns.empty()Check failed: format_strFormat string cannot be emptyCheck failed: falseCheck failed: std::string(schema->format) == "+s"Column data type not supported by XGBoostPdMdMdMdMdM$OdMdMOdMdMdMdMdMdMOdMdMdMdMdMdMdMdMdMdMdMdMdMdMdMPdMdMNNdMNdMdMNdMdMdMdMdMdM,N/__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_modelscannot create std::vector larger than max_size()i < Dj_strides.size() == j_shape.size()stride and shape don't match.ptr % alignment == 0Input pointer misalignment.streamEmpty data with non-zero shape.Check failed: mask_it == array.cend() || IsA(mask_it->second)Masked array is not yet supported.Check failed: m == 1 || n == 1n_bits == nShape of bit mask doesn't match data shape. XGBoost doesn't support internal broadcasting.__Cannot find argument '', Possible Arguments: ---------------- : Check failed: columns_ == data::kAdapterUnknownSize || columns_ == batch.columnsNumber of columns between batches changed from St11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EESt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EEN4dmlc5ErrorEN4dmlc6StreamEN4dmlc10SeekStreamEN4dmlc7istream5InBufEN4dmlc7istreamEN4dmlc10ParamErrorEN4dmlc9parameter16FieldAccessEntryEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIiEEiEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIiEEiEEN4dmlc9parameter10FieldEntryIiEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIbEEbEEN4dmlc9parameter10FieldEntryIbEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIfEEfEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIfEEfEEN4dmlc9parameter10FieldEntryIfEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIdEEdEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIdEEdEEN4dmlc9parameter10FieldEntryIdEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIlEElEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIlEElEEN4dmlc9parameter10FieldEntryIlEEN5rabit5utils19MemoryFixSizeBufferEN5rabit5utils18MemoryBufferStreamEN4dmlc8DataIterIN7xgboost4data15CSRAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_15CSRAdapterBatchEEEN7xgboost4data10CSRAdapterEN4dmlc8DataIterIN7xgboost4data17DenseAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_17DenseAdapterBatchEEEN7xgboost4data12DenseAdapterEN4dmlc8DataIterIN7xgboost4data17ArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_17ArrayAdapterBatchEEEN7xgboost4data12ArrayAdapterEN4dmlc8DataIterIN7xgboost4data20CSRArrayAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_20CSRArrayAdapterBatchEEEN7xgboost4data15CSRArrayAdapterEN4dmlc8DataIterIN7xgboost4data15CSCAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_15CSCAdapterBatchEEEN7xgboost4data10CSCAdapterEN4dmlc8DataIterIN7xgboost4data21DataTableAdapterBatchEEEN7xgboost4data6detail19SingleBatchDataIterINS0_21DataTableAdapterBatchEEEN7xgboost4data16DataTableAdapterEN4dmlc8DataIterIN7xgboost4data16FileAdapterBatchEEEN7xgboost4data18ArrowColumnarBatchEN4dmlc8DataIterISt6vectorISt10unique_ptrIN7xgboost4data18ArrowColumnarBatchESt14default_deleteIS5_EESaIS8_EEEEN7xgboost4data24RecordBatchesIterAdapterEN7xgboost4data12DMatrixProxyEN4dmlc9parameter14FieldEntryBaseINS0_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/c_apiBUILTIN_PREFETCHMM_PREFETCH_PRESgradient_booster/__w/ml-builds/ml-builds/xgboost/src/collective/rabit_communicator.hUnknown allreduce operationUnknown data type$H|HHIlII\GG/__w/ml-builds/ml-builds/xgboost/src/collective/communicator.h is greater than world_size - 1: =1=0Failed to initialize RabitWorld size is less than 1.Rank is less than 0.XGBOOST_COMMUNICATORrabitfederatedUnknown communicator type /__w/ml-builds/ml-builds/xgboost/src/collective/communicator.ccXGBoost is not compiled with Federated Learning support.N7xgboost10collective12CommunicatorEN7xgboost10collective16NoOpCommunicatorEN7xgboost10collective17RabitCommunicatorEXGBOOST_COMMUNICxgboost_communic/__w/ml-builds/ml-builds/xgboost/src/collective/socket.ccgetsockopt(handle_, SOL_SOCKET, SO_DOMAIN, reinterpret_cast(&domain), &len)static_cast(socket.Domain()) == static_cast(addr.Domain())Check failed: !this->IsClosed()str.size() < std::numeric_limits::max()this->SendAll(&len, sizeof(len)) == sizeof(len)this->RecvAll(&len, sizeof(len)) == sizeof(len)Failed to get addr info for: 127.0.0.10.0.0.0::1::Unknown IA family.sendFailed to send string length.bytes == str.size()Failed to send string.recvFailed to recv string length.bytes == lenFailed to recv string./__w/ml-builds/ml-builds/xgboost/include/xgboost/collective/socket.hFailed to call `system::CloseSocket(handle_)`: NaNInfinity0E0@je _vH@0ļ4&k7y؅W4Ngm=`X@xPMJ- yCx(,*42q0/'|!1錠9Y>R$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.{$~ۃ6/l##ՂF!00010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899vector::_M_fill_insert/__w/ml-builds/ml-builds/xgboost/src/common/column_matrix.ccgmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_val?/__w/ml-builds/ml-builds/xgboost/src/common/threading_utils.hentries_per_columns.size() == static_cast(n_columns)column_sizes_tloc[i].size() == static_cast(n_columns)/__w/ml-builds/ml-builds/xgboost/src/common/hist_util.ccentries_per_column.size() == info.num_col_/__w/ml-builds/ml-builds/xgboost/src/common/../data/proxy_dmatrix.h/__w/ml-builds/ml-builds/xgboost/src/common/quantile.hCheck failed: nlevel <= std::max(static_cast(1), static_cast(limit_size * eps))invalid init parameter/__w/ml-builds/ml-builds/xgboost/src/common/hist_util.hUnreachable@)ASortedSketchCont/__w/ml-builds/ml-builds/xgboost/src/common/host_device_vector.ccSize() == other.Size()Size() == other.size()basic_string::substrCheck failed: outpointer_ <= buffer_.size()file://Opening %s: __pos (which is %zu) > this->size() (which is %zu)/__w/ml-builds/ml-builds/xgboost/src/common/io.cc/__w/ml-builds/ml-builds/xgboost/src/common/io.hNot implementedN7xgboost6common16PeekableInStreamEN7xgboost6common15FixedSizeStreamE/__w/ml-builds/ml-builds/xgboost/src/common/json.cc can not be indexed by string. can not be indexed by Integer./__w/ml-builds/ml-builds/xgboost/include/xgboost/string_view.hHigh precision number is not supported.Check failed: ret.ec == std::errc()` is not supported for typed array.I32ArrayObject of type , around character position: , "beg <= size_\n\0Expecting digitf64 is not supported.Unknown construct \\\"\b\f\r\t\u%04xch != -1cursor_.Pos(): raw_str_.size():| <\4T&p'$l%$*'$$_($$$$$$%l% +$$$$>%G+$$$$$$$$P)$$$$M'$$*$$$$$$$$$$$$$$&,0................./..././/", got: "EOF"\0"N7xgboost5ValueEN7xgboost10JsonStringEN7xgboost9JsonArrayEN7xgboost10JsonObjectEN7xgboost10JsonNumberEN7xgboost11JsonIntegerEN7xgboost8JsonNullEN7xgboost11JsonBooleanEN7xgboost10JsonReaderEN7xgboost10JsonWriterEN7xgboost9UBJReaderEN7xgboost9UBJWriterEN7xgboost14JsonTypedArrayIfLNS_5Value9ValueKindE7EEEN7xgboost14JsonTypedArrayIhLNS_5Value9ValueKindE8EEEN7xgboost14JsonTypedArrayIiLNS_5Value9ValueKindE9EEEN7xgboost14JsonTypedArrayIlLNS_5Value9ValueKindE10EEE 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 lPesudoHuberParamp)))*(*8*`)P*`*H*`),,,D,d,,,,, -++/__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=max_cat + 1 >= n_categoriesfeature_ptr.front() == 0rank_size == totalPushColPagesketch->temp.size <= max_size, stemp.size=HostSketchContainer/__w/ml-builds/ml-builds/xgboost/src/common/../data/adapter.hUnknown data table type.ȱ @0h\D, ܹ4tp`P tdLhX8 xx4t,`H0 \D\,pXH8(invalid 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.group_ptr.size() >= 2group_ptr.back() == n_samplessrc.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].dataworker_segments.size() >= 1Check failed: worker_feature.data()SketchContainerImplcolumns_size_.size() != 0n_threads_ >= 1AllReducen_columns == sketches_.size()num_cuts.size() == 0Number of columns differs across workersMakeCutscuts->cut_values_.HostVector().size() <= std::numeric_limits::max()cut_size > cuts->cut_ptrs_.HostVector().back()count <= total_entriesPushRowPagesketches_.size() == n_columns0 x@4$Dfloat32float64bool8int32int8int16int64p)8)))((((((P)FFFFFFGK_o;o:A>/__w/ml-builds/ml-builds/xgboost/src/common/random.harray.size() == weights.size()/__w/ml-builds/ml-builds/xgboost/src/common/random.ccfeatures.size() > 0TSt19_Sp_make_shared_tagSt23_Sp_counted_ptr_inplaceIN7xgboost16HostDeviceVectorIjEESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE߰߰߰߰75//__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./parameter.henum_back_map_.count(value) != 0UValue not found in enum declaredInvalid Input: '', valid values are: /__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././strtonum.hEnum exisit!) Enums: ), N4dmlc9parameter10FieldEntryIN7xgboost6common27ProbabilityDistributionTypeEEEaft_loss_distribChoice of distribution for the noise term in Accelerated FailureScaling factor used to scale the distribution in Accelerated Fai/sys/fs/cgroup/cpu/cpu.cfs_quota_us/sys/fs/cgroup/cpu/cpu.cfs_period_usTimer for calls @ us======== Monitor ( ======== did not get stopped properly..A/src/common/time/__w/ml-builds/ml-builds/xgboost/src/common/version.ccfi->Read(&read[0], verstr.size()) == verstr.size()Check failed: fi->Read(&major)Check failed: fi->Read(&minor)Check failed: fi->Read(&patch)Invaid version format in loaded JSON object: Incorrect version format found in binary file. Binary file from XGBoost < 1.0.0 is no longer supported. Please generate it agai`Hب 0ب̪td4DTȫ(ptL̳|T,ԲP0ضpP0еp, ļdD$DH(ȾxX `lT<Ŀ`@ (L4$X@``lT,< `@ 8dD$T`@xXxlL, TpP0X<tT4Tx hht\ ,D h0@@4tt(PP<,Tl,P@`p@TRead(&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 + 1 must be equal to number of columns.cache_file.find('#') == std::string::nposOnly one `#` is allowed in file path for cache file specification.No format parameter is provided in input uri, but found file extension: Consider providing a uri parameter: filename?format=No format parameter is provided in input uri. Choosing default parser in dmlc-core. Consider providing a uri parameter like: filename?format=csvthis->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.Check failed: array.valid.Size() == 0Meta info like label or weight can not have missing value.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.`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.hP 0HС|T<$ ܢةp0ȨtLT\$num_col_Length of Check failed: infoUnknown feature info name: .rbasic_string::basic_stringautoLoad part of data partscsvlibsvm . Encountered parser error: that.group_ptr_.size() != 0Check failed: t.CContiguous()Incorrect size for labels.Check failed: non_decUnknown key for MetaInfo: Check failed: key to be a tensor; got a scalar is no longer supported. again.major >= 1minor >= 6MetaInfo: invalid formatnum_field >= expectedfields.)/__w/ml-builds/ml-builds/xgboost/src/data/file_iterator.hCheck failed: !type_.empty()/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.hCheck failed: page_/__w/ml-builds/ml-builds/xgboost/src/data/../common/common.h/__w/ml-builds/ml-builds/xgboost/src/data/../data/adapter.hL, Data()->Size() == detail::CalcSize(this->shape_)Inconsistent size after modification.shape[i] == r.Shape(i)<Check failed: parser_qidkey >= builder_base_row_offset%$%(%p%"P$\4444 5<5d555$3$4format.front() == '.'Unknown format type fi->Tell() == offsetRead a page in seconds./__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_writer.hCheck failed: fmt->Read(page.get(), fi.get())Check failed: !cache_info_->written MB written in Check failed: !at_end_n_prefetch_batches > 0total batches:fetch_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: validInput data contains `inf` or `nan`/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././././any.hCheck failed: type_ != nullptrCheck failed: *(type_->ptype_info) == typeid(T)/__w/ml-builds/ml-builds/xgboost/src/data/../data/proxy_dmatrix.hThe any container is empty requested=The stored type mismatch stored=Unknown type: count_ == n_batches_Check failed: proxy_this->count_ >= 1source_->Iter() == this->count_N7xgboost10SparsePageEN7xgboost7DMatrixEN7xgboost4data11FileAdapterEN7xgboost17BatchIteratorImplINS_11EllpackPageEEENSt13__future_base13_State_baseV2ENSt13__future_base21_Async_state_commonV2ESt10shared_ptrIN7xgboost4data15CSRArrayAdapterEESt10shared_ptrIN7xgboost4data12ArrayAdapterEEN7xgboost4data20SparsePageSourceImplINS_11EllpackPageEEEN7xgboost4data18PageSourceIncMixInINS_11EllpackPageEEEN7xgboost4data17EllpackPageSourceENSt13__future_base7_ResultISt10shared_ptrIN7xgboost10SparsePageEEEENSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS4_10SparsePageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS7_EEENSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS4_10SparsePageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS7_EEESt23_Sp_counted_ptr_inplaceIN7xgboost10SparsePageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS5_10SparsePageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEESaISF_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS5_10SparsePageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEESaISF_ELN9__gnu_cxx12_Lock_policyE2EENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultISt10shared_ptrIN7xgboost10SparsePageEEEENS_12_Result_base8_DeleterEENSt6thread8_InvokerISt5tupleIJZNS4_4data20SparsePageSourceImplIS5_E9ReadCacheEvEUlvE_EEEES6_EENSt6thread11_State_implINS_8_InvokerISt5tupleIJZNSt13__future_base17_Async_state_implINS1_IS2_IJZN7xgboost4data20SparsePageSourceImplINS5_10SparsePageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEC4EOSC_EUlvE_EEEEEE P?eA/__w/ml-builds/ml-builds/xgboost/src/data/ellpack_page.ccInternal Error: XGBoost is not compiled with CUDA but EllpackPage is required@pȶض̷$Ddt/__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.hhit_count.size() == n_bins_totalCheck failed: p_fmat->SingleColBlock()\\h\X\H\8\[\\(\[^^\^L^,^^]]]\^(bbaaaaaxa`a`8b,ddccccccdcbDdCheck failed: columns_Check failed: !sorted_sketchrow_ptr.size() == 0vector::_M_fill_inserthP(D$dtdd(pX8hCheck failed: binTypeSize == kUint8BinsTypeSize || binTypeSize == kUint16BinsTypeSize || binTypeSize == kUint32BinsTypeSizeRaw GHistIndex binary data format.N7xgboost4data16SparsePageFormatINS_16GHistIndexMatrixEEEN7xgboost4data19GHistIndexRawFormatE*N7xgboost4dataL30__make_GHistIndexPageFmt_raw__MUlvE_E/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././any.h/__w/ml-builds/ml-builds/xgboost/src/data/proxy_dmatrix.h/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.h/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_writer.h/__w/ml-builds/ml-builds/xgboost/src/data/gradient_index_page_source.cccount_ == source_->Iter()cuts_.Values().size() != 0N7xgboost17BatchIteratorImplINS_16GHistIndexMatrixEEEN7xgboost4data20SparsePageSourceImplINS_16GHistIndexMatrixEEEN7xgboost4data18PageSourceIncMixInINS_16GHistIndexMatrixEEEN7xgboost4data23GradientIndexPageSourceENSt13__future_base7_ResultISt10shared_ptrIN7xgboost16GHistIndexMatrixEEEENSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS4_16GHistIndexMatrixEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS7_EEENSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS4_16GHistIndexMatrixEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS7_EEESt15_Sp_counted_ptrIPN7xgboost16GHistIndexMatrixELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost16GHistIndexMatrixESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS5_16GHistIndexMatrixEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEESaISF_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS5_16GHistIndexMatrixEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEESaISF_ELN9__gnu_cxx12_Lock_policyE2EENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultISt10shared_ptrIN7xgboost16GHistIndexMatrixEEEENS_12_Result_base8_DeleterEENSt6thread8_InvokerISt5tupleIJZNS4_4data20SparsePageSourceImplIS5_E9ReadCacheEvEUlvE_EEEES6_EENSt6thread11_State_implINS_8_InvokerISt5tupleIJZNSt13__future_base17_Async_state_implINS1_IS2_IJZN7xgboost4data20SparsePageSourceImplINS5_16GHistIndexMatrixEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEC4EOSC_EUlvE_EEEEEE/src/data/sparse66 7h7x7767776d8|88888949\9$8D8HG0GGFFFFFpFEXGtQ\QInfo().num_col_ == n_featuresInvalid ref DMatrix, different number of features.Inconsistent max_bin between Quantile DMatrix and Booster:Check failed: !param.regen && param.hess.empty()`sparse_threshold` can not be changed when `QuantileDMatrix` is used instead of `DMatrix`.page.row_ptr.size() == h_offset.size()/__w/ml-builds/ml-builds/xgboost/src/data/../common/../data/../common/hist_util.hInconsistent number of columns.Check failed: std::none_of(column_sizes.cbegin(), column_sizes.cend(), [&](auto f) { return f > accumulated_rows; })Something went wrong during iteration.Data must has at least 1 column.accumulated_rows == Info().num_row_proxy->Info().labels.Size() == 0Iterative DMatrix must have at least 1 batch.All batch should be on the same device.pP0pT4|dtxX8HdD||pP0@\ <  t t h H (  8 T4  l  l@p@\D$DthH(P8'&D&&%%<#|%T%%<#$$$$x$`$@$ $##%4))((((d(L(('T)/.@..--8+x-P--8+,,,,t,\,<,,++,0110000`0H00/P1,87\747 76T46l66T465555x5X585446L:,:9999|9d998l:/__w/ml-builds/ml-builds/xgboost/src/data/iterative_dmatrix.hSlicing DMatrix is not supported for Quantile DMatrix./__w/ml-builds/ml-builds/xgboost/src/data/simple_batch_iterator.hCheck failed: page_ != nullptrXC@C CCBBBBB@pCCheck failed: proxy_handleInvalid proxy handle.Check failed: typedDO$ONNNN|N\N4NM\OOnly `hist` and `gpu_hist` tree method can use `QuantileDMatrix`.Check failed: ref_Check failed: p_cutsCheck failed: ellpack_n_features == num_cols()n_features >= 1Check failed: p_sketchrbegin == Info().num_row_d == batch_param_.gpu_id/__w/ml-builds/ml-builds/xgboost/src/data/../common/../data/../common/threading_utils.h/__w/ml-builds/ml-builds/xgboost/src/data/../common/../data/gradient_index.h/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/any.hCheck failed: !std::isnan(sparse_thresh)ԟğtdL4еh`(\L,l`H0 St14default_deleteIN7xgboost16GHistIndexMatrixEEN7xgboost4data16IterativeDMatrixEN7xgboost4data23SimpleBatchIteratorImplINS_11EllpackPageEEEN7xgboost4data23SimpleBatchIteratorImplINS_16GHistIndexMatrixEEEN7xgboost17BatchIteratorImplINS_13ExtSparsePageEEEN7xgboost4data23SimpleBatchIteratorImplINS_13ExtSparsePageEEESt19_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: on_hostNot implemented on device.@FEHEEE@HEHHEEEEEEEEEEEH0IEEIEEJEEEHJEEEEEEJJSt19__shared_ptr_accessIN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt19__shared_ptr_accessIN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2ELb0ELb0EESt12__shared_ptrIN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt12__shared_ptrIN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data12ArrayAdapterELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data15CSRArrayAdapterELN9__gnu_cxx12_Lock_policyE2EEUnsigned integerComplex floatingparam.gpu_id >= 0param.max_bin >= 2param.gpu_id == -1invalid input file formattmagic == kMagicggggThhi\ii jdj/__w/ml-builds/ml-builds/xgboost/src/data/adapter.hCheck failed: data_ && row_idx < length_Column is empty or out-of-bound index of the column/__w/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.ccCheck failed: r != BatchParam{}Batch parameter is not initialized.Generating new Gradient Index.batch_param_.hess.data() == param.hess.data()Check failed: in_stream->Read(&tmagic)invalid format, magic number mismatchoffset_vec.back() == info_.num_nonzero_Check failed: data_Column is empty/__w/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.hCheck failed: (std::is_same::value)Expecting CSCAdapterN7xgboost7CSCPageEN7xgboost13SortedCSCPageEN7xgboost4data6ColumnEN7xgboost4data15PrimitiveColumnIaEEN7xgboost4data15PrimitiveColumnIhEEN7xgboost4data15PrimitiveColumnIsEEN7xgboost4data15PrimitiveColumnItEEN7xgboost4data15PrimitiveColumnIiEEN7xgboost4data15PrimitiveColumnIjEEN7xgboost4data15PrimitiveColumnIlEEN7xgboost4data15PrimitiveColumnImEEN7xgboost4data15PrimitiveColumnIfEEN7xgboost4data15PrimitiveColumnIdEEN7xgboost4data13SimpleDMatrixEN7xgboost17BatchIteratorImplINS_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_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnIaEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnIhEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnIsEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnItEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnIiEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnIjEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnIlEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnImEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnIfEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data15PrimitiveColumnIdEESaIS3_ELN9__gnu_cxx12_Lock_policyE2EEGGGG/src/data/simple/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.ccCheck failed: sparse_page_source_Check failed: ghist_index_source_/__w/ml-builds/ml-builds/xgboost/src/data/./sparse_page_dmatrix.hSlicing DMatrix is not supported for external memory./__w/ml-builds/ml-builds/xgboost/src/data/./../common/common.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:iter_.Next() == 1Must have at least 1 batch.-rinfo_.num_col_ != 0this->Info().num_col_ != 0.gradient_index.pagecuts.Values().size() != 0N7xgboost4data20SparsePageSourceImplINS_10SparsePageEEEN7xgboost4data16SparsePageSourceEN7xgboost4data20SparsePageSourceImplINS_7CSCPageEEEN7xgboost4data18PageSourceIncMixInINS_7CSCPageEEEN7xgboost4data13CSCPageSourceEN7xgboost4data20SparsePageSourceImplINS_13SortedCSCPageEEEN7xgboost4data18PageSourceIncMixInINS_13SortedCSCPageEEEN7xgboost4data19SortedCSCPageSourceEN7xgboost4data17SparsePageDMatrixENSt13__future_base7_ResultISt10shared_ptrIN7xgboost7CSCPageEEEENSt13__future_base7_ResultISt10shared_ptrIN7xgboost13SortedCSCPageEEEENSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS4_7CSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS7_EEENSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS4_7CSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS7_EEENSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS4_13SortedCSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS7_EEENSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS4_13SortedCSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS7_EEESt15_Sp_counted_ptrIPN7xgboost4data5CacheELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost4data23GradientIndexPageSourceELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data16SparsePageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data13CSCPageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost4data19SortedCSCPageSourceESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost7CSCPageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceIN7xgboost13SortedCSCPageESaIS1_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS5_7CSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEESaISF_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS5_7CSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEESaISF_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base17_Async_state_implINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS5_13SortedCSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEESaISF_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base15_Deferred_stateINSt6thread8_InvokerISt5tupleIJZN7xgboost4data20SparsePageSourceImplINS5_13SortedCSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEESaISF_ELN9__gnu_cxx12_Lock_policyE2EENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultISt10shared_ptrIN7xgboost7CSCPageEEEENS_12_Result_base8_DeleterEENSt6thread8_InvokerISt5tupleIJZNS4_4data20SparsePageSourceImplIS5_E9ReadCacheEvEUlvE_EEEES6_EENSt6thread11_State_implINS_8_InvokerISt5tupleIJZNSt13__future_base17_Async_state_implINS1_IS2_IJZN7xgboost4data20SparsePageSourceImplINS5_7CSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEC4EOSC_EUlvE_EEEEEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultISt10shared_ptrIN7xgboost13SortedCSCPageEEEENS_12_Result_base8_DeleterEENSt6thread8_InvokerISt5tupleIJZNS4_4data20SparsePageSourceImplIS5_E9ReadCacheEvEUlvE_EEEES6_EENSt6thread11_State_implINS_8_InvokerISt5tupleIJZNSt13__future_base17_Async_state_implINS1_IS2_IJZN7xgboost4data20SparsePageSourceImplINS5_13SortedCSCPageEE9ReadCacheEvEUlvE_EEEESt10shared_ptrIS8_EEC4EOSC_EUlvE_EEEEEE.sorted.col.page/__w/ml-builds/ml-builds/xgboost/src/data/sparse_page_raw_format.ccCheck failed: page.offset.Size() != 0 && offset_vec[0] == 0offset_vec.back() == page.data.Size()Raw binary data format.page->offset.Size() != 0UInvalid SparsePage filen_bytes == (page->data).Size() * sizeof(Entry)N7xgboost4data16SparsePageFormatINS_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 current booster.Slice is not supported by current booster.model/__w/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.hfi->Read(¶m_, sizeof(param_)) == sizeof(param_)DoBoostlayer_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_perbatchlong (non-negative)Maximum rows per batch.Update algorithm for linear model. One of shotgun/coord_descentStop if largest weight update is smaller than this number./__w/ml-builds/ml-builds/xgboost/src/gbm/../common/common.hLoading configuration on a CPU only machine. Changing updater to `coord_descent`.GBLineargblinear_train_paramCheck failed: this->updater_N4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEES8_EEN4dmlc9parameter10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEEN7xgboost5ModelEN7xgboost12ConfigurableEN7xgboost15GradientBoosterEN7xgboost3gbm8GBLinearE*N7xgboost3gbmL36__make_GradientBoosterReg_GBLinear__MUlPKNS_17LearnerModelParamEPKNS_16GenericParameterEE_Eboosted_roundsN7xgboost3gbm13GBLinearModelEDeprecatedGBLinedeprecated_num_fint (non-negativdeprecated_num_oUnknown gbm type /__w/ml-builds/ml-builds/xgboost/src/gbm/gbm.cc/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree.ccTree method is automatically selected to be 'approx' for distributed training.Tree method is automatically set to 'approx' since external-memory data matrix is used.Tree method is automatically selected to be 'approx' for faster speed. To use old behavior (exact greedy algorithm on single machine), set tree_method to 'exact'.Check failed: !updaters_.empty()Tree method is selected to be 'hist', which uses a single updater grow_quantile_histmaker.XGBoost version not compiled with OneAPI support.Data is on CUDA device, but XGBoost is not compiled with CUDA support.tree_end <= model_.trees.size()ups.size() == updaters_.size() mismatched updater sequence. get(in["name"]) == "gbtree"this->model_.learner_model_param->num_feature != 0this->model_.trees_to_update.size() == this->model_.trees.size() trees remain. Slice the model before making update if you only want to update a portion of trees.Check failed: !updaters_.front()->CanModifyTree()can not be used to create new trees. Set `process_type` to `update` if you want to update existing trees.Check failed: up->CanModifyTree()can not be used to modify existing trees. Set `process_type` to `default` if you want to build new trees.model_.trees.size() < model_.trees_to_update.size()No more tree left for updating. For updating existing trees, boosting rounds can not exceed previous training roundsgpair->Size() == p_fmat->Info().num_row_Mismatching size between number of rows from input data and size of gradient vector.Check failed: this->configured_Check failed: tparam_.GetInitialised()Current objective doesn't support external memory.in_gpair->Size() % ngroup == 0Umust have exactly ngroup * nrow gpairsDANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.Loading from a raw memory buffer on CPU only machine. Changing predictor to auto. 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`.Changing updater from `grow_gpu_hist` to `grow_quantile_histmaker`.Tree booster, gradient boosted trees.Using tree method: grow_histmakergrow_colmaker,prunegrow_quantile_histmakergrow_gpu_histUnknown tree_method () detectedCheck failed: configured_Check failed: cpu_predictor_out_preds->version == 0Invalid number of trees.Internal Error: Specified updaters: Actual updaters: Check failed: p_gbtreelayer_trees != 0layer_end > layer_beginstep >= 1Not all trees are updated, GBTreeModelParamGBTreeTrainParamDartTrainParamUpdater: `` Using updaters: BoostNewTreesngroup != 0GBTreegbtree_train_paramspecified_updaterTree booster, dart.`P*N7xgboost3gbmL34__make_GradientBoosterReg_GBTree__MUlPKNS_17LearnerModelParamEPKNS_16GenericParameterEE_E*N7xgboost3gbmL32__make_GradientBoosterReg_Dart__MUlPKNS_17LearnerModelParamEPKNS_16GenericParameterEE_E/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././parameter.hweight_dropcpu_predictorgpu_predictorCheck failed: successCurrent Predictor: /__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree.htree_begin <= tree_endmodel_.param.num_parallel_tree != 0model_.learner_model_param->num_output_group != 0tree_begin == 0Predict interaction contribution supports only iteration end: (0, n_iteration), using model slicing instead.Predict contribution supports only iteration end: (0, n_iteration), using model slicing instead.Predict leaf supports only iteration end: (0, n_iteration), use model slicing instead.Unsupported data type for inplace predict.get(in["name"]) == "dart"Check failed: predictori >= p_out_preds->versionp_out_preds->predictions.Size() == predts.predictions.Size()predts.predictions.Size() == p_out_preds->predictions.Size()/__w/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./././strtonum.hin_it < tree_endCheck failed: p_dartCheck failed: p_dart->weight_drop_.empty()vector::reservedrop trees, weight = num_treessize_leaf_vectorNumber of features used for training and prediction.Number of parallel trees constructed during each iteration. This option is used to support boosted random forest.Reserved option for vector tree. has not been registered in Alias updater_seqTree updater sequence.process_typedefaultupdateoneapi_predictorPredictor algorithm typetree_methodapproxexactWhether to run the normal boosting process that creates new trees, or to update the trees in an existing model.Choice of tree construction method.sample_typeuniformweightednormalize_typeforestrate_dropone_dropbooleanskip_droplearning_rateetaDifferent types of sampling algorithm.Different types of normalization algorithm.Fraction of trees to drop during the dropout.Whether at least one tree should always be dropped during the dropout.Probability of skipping the dropout during a boosting iteration.Learning rate(step size) of update.cannot create std::deque larger than max_size()idx <= total_n_treesInvalid tree index.total_gaintotal_coverUnknown feature importance type, expected one of: {"weight", "total_gain", "total_cover", "gain", "cover"}, got: dart_train_paramN4dmlc9parameter10FieldEntryIN7xgboost10TreeMethodEEEN4dmlc9parameter10FieldEntryIN7xgboost15TreeProcessTypeEEEN4dmlc9parameter10FieldEntryIN7xgboost13PredictorTypeEEEN7xgboost3gbm6GBTreeEN7xgboost3gbm4DartE?A;?/__w/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.ccparam.num_trees == static_cast(trees.size())fi->Read(¶m, sizeof(param)) == sizeof(param)fi->Read(dmlc::BeginPtr(tree_info), sizeof(int32_t) * param.num_trees) == sizeof(int32_t) * param.num_treesparam.num_trees == static_cast(trees.size())GBTree: invalid model fileCheck failed: ctx_N7xgboost3gbm11GBTreeModelEgbtree_model_parFlag to print out detailed breakdown of runtime.Whether to use RAPIDS Memory Manager to allocate GPU memory in XGlobalConfiguratCheck failed: n_classes <= 1 || n_targets <= 1Multi-class multi-output is not yet supported. n_classes:Check failed: common::AsConst(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(), n_targets:base_score_.Size() == 1LearnerModelParamLegacyGenericParameterLearnerTrainParam/__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 current objective functionCheck failed: ret.ec == std::errc{}num_featurenum_classnum_targetboost_from_averageCheck failed: learner_model_param_.Initialized()learner_model_param_.BaseScore(this->Ctx()).Size() != 0ModelConfigCall 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_Empty dataset at worker: Global bias of the model.int (non-negative)Number of features in training data, this parameter will be automatically detected by learner.Number of class option for multi-class classifier. By default equals 0 and corresponds to binary classifier.Number of target for multi-target regression.Whether we should calculate the base score from training data.seedlongrandom_stateseed_per_iterationNumber of threads to use.n_jobsfail_on_invalid_gpu_idvalidate_parametersRandom number seed during training.Seed PRNG determnisticly via iterator number.The primary GPU device ordinal.Fail with error when gpu_id is invalid.Enable checking whether parameters are used or not.dsplitdisable_default_eval_metricreg:squarederrorData split mode for distributed training.Flag to disable default metric. Set to >0 to disableGradient booster used for training.Objective function used for obtaining gradient.;metricsbinfmulti:softprobnum_output_groupmulti:softmaxcount:poisson0.7learner_train_paramgeneric_paramBoostOneIterCheck failed: tparam_.dsplit != DataSplitMode::kAutoPrecondition violated; dsplit cannot be 'auto' in distributed modeColumn-wise data split is currently not supported.Check 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: ptrlearner_model_param_.BaseScore(Ctx()).Size() != 0Check failed: !std::isnan(mparam_.base_score)Check failed: !std::isinf(mparam_.base_score)multiple_predictions <= 1Check failed: gbm_ != nullptrPerform one kind of prediction at a time.Predict must happen after Load or configurationUpdateOneIterPredictRawPredictionsGetGradientGradientsEvalOneIterCheck failed: matrix.first features or greatermparam_.num_feature != 0Check failed: !matrix.second.ref.expired()num_col <= static_cast(std::numeric_limits::max())Unfortunately, XGBoost does not support data matrices with 0 feature is supplied. Are you using raw Booster interface?Check failed: IsA(in) If you are loading a serialized model (like pickle in Python, RDS in R) generated by older 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/latest/tutorials/saving_model.html for more details about differences between saving model and serializing. Found 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. ConfigureLearnernum_roundCONFIG-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_layer >= 0best_iterationbest_scoreUnsupported prediction type:fixed_size->Read(&buffer[0], size) == sizebs64header != "bs64"fp.Read(&header[0], 4) == 4UInvalid model formatSAVED_PARAM_count_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)N4dmlc12SerializableEN7xgboost7LearnerEN4dmlc9parameter10FieldEntryIN7xgboost13DataSplitModeEEEN7xgboost20LearnerConfigurationEN7xgboost9LearnerIOEN7xgboost11LearnerImplEUnknown 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.hUpdateFeature/__w/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.hunknown coordinate selector: XP0N7xgboost13LinearUpdaterEN7xgboost6linear15FeatureSelectorEN7xgboost6linear21CyclicFeatureSelectorEN7xgboost6linear22ShuffleFeatureSelectorEN7xgboost6linear21RandomFeatureSelectorEN7xgboost6linear21GreedyFeatureSelectorEN7xgboost6linear22ThriftyFeatureSelectorEN7xgboost6linear17CoordinateUpdaterE*N7xgboost6linearL43__make_LinearUpdaterReg_CoordinateUpdater__MUlvE_EThe number of top features to select in 'thrifty' feature_selector. The value of zero means using all the featurCoordinateUpdatelinear_train_parcoordinate_param/__w/ml-builds/ml-builds/xgboost/src/linear/updater_shotgun.ccUnsupported feature selector for shotgun updater. Supported options are: {cyclic, shuffle}Uh$hg{gvhUpdate 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/../common/threading_utils.hinfo.group_ptr_.size() >= 2n_classes != 0labels.Shape(1) == 1AUC doesn't support multi-target model./__w/ml-builds/ml-builds/xgboost/src/metric/auc.hPR-AUC supports only binary relevance for learning to rank.auc <= 1.0finfo.weights_.Size() == info.group_ptr_.size() - 1info.group_ptr_.back() == info.labels.Size()Dataset is empty, or contains only positive or negative samples.auc <= 1Total AUC across groups: , valid groups: auc <= local_areaN7xgboost6MetricEN7xgboost6metric7EvalAUCINS0_10EvalROCAUCEEEN7xgboost6metric10EvalROCAUCEN7xgboost6metric7EvalAUCINS0_9EvalPRAUCEEEN7xgboost6metric9EvalPRAUCEN7xgboost6metric26__make_MetricReg_EvalAUC__MUlPKcE_EN7xgboost6metric24__make_MetricReg_AUCPR__MUlPKcE_E/src/metric/auc.??????mphegamma-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 metricinfo.labels.Shape(0) == info.num_row_slope for pseudo huber cannot be 0.slope != 0.0Rooted mean square error.Rooted mean square log error.Mean absolute error.Mean Pseudo-huber error.Binary classification error.tweedie-nloglikpreds.Size() == info.labels.Size()label and prediction size not match, hint: use merror or mlogloss for multi-class classificationinfo.labels.Shape(1) != 0N7xgboost6metric15PseudoErrorLossEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowRMSEEEEN7xgboost6metric13EvalEWiseBaseINS0_12EvalRowRMSLEEEEN7xgboost6metric13EvalEWiseBaseINS0_10EvalRowMAEEEEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowMAPEEEEN7xgboost6metric13EvalEWiseBaseINS0_14EvalRowLogLossEEEN7xgboost6metric13EvalEWiseBaseINS0_20EvalPoissonNegLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_17EvalGammaDevianceEEEN7xgboost6metric13EvalEWiseBaseINS0_16EvalGammaNLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_9EvalErrorEEEN7xgboost6metric13EvalEWiseBaseINS0_18EvalTweedieNLogLikEEEN7xgboost6metric23__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_E$$tI$t@pseudo_huber_parư>/__w/ml-builds/ml-builds/xgboost/src/metric/metric.ccCannot find a GPU metric builder for metric . Resorting to the CPU builderUnknown metric function /src/metric/metrmerrormlogloss/__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-nloglikNegative log partial likelihood of Cox proportional hazards model./__w/ml-builds/ml-builds/xgboost/src/metric/rank_metric.ccAMS must be in format ams@kams@%u[-]?prelabel size predict size not matchmust specify group when constructing rank fileEvalRank: group structure must match number of predictiongptr.size() != 0Ugptr.back() == preds.Size()Check failed: tparam_AMS metric for higgs.precision@k for rank.ndcg@k for rank.map@k for rank.Check failed: !collective::IsDistributed()Cox metric does not support distributed evaluationmetric AMS do not support distributed evaluationbest-ams-ratio=G(#hN7xgboost6metric14EvalRankConfigEN7xgboost6metric7EvalAMSEN7xgboost6metric8EvalRankEN7xgboost6metric13EvalPrecisionEN7xgboost6metric8EvalNDCGEN7xgboost6metric7EvalMAPEN7xgboost6metric7EvalCoxEN7xgboost6metric22__make_MetricReg_AMS__MUlPKcE_EN7xgboost6metric28__make_MetricReg_Precision__MUlPKcE_EN7xgboost6metric23__make_MetricReg_NDCG__MUlPKcE_EN7xgboost6metric22__make_MetricReg_MAP__MUlPKcE_EN7xgboost6metric22__make_MetricReg_Cox__MUlPKcE_E/src/metric/rank$@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/adaptive.hCheck failed: quantiles.empty() || quantiles.size() == n_leafCheck failed: tree[nidx].IsLeaf()/__w/ml-builds/ml-builds/xgboost/src/objective/adaptive.cc/__w/ml-builds/ml-builds/xgboost/src/objective/../common/stats.hCheck failed: alpha >= 0 && alpha <= 1Check failed: h_row_set.empty()begin_pos <= sorted_pos.size()Check failed: !position.empty()h_node_ptr.back() <= info.num_row_/__w/ml-builds/ml-builds/xgboost/src/objective/../common/threading_utils.hk + 1 < h_node_ptr.size()k >= 0nptr.size() > 0n_unique == n_leaf؈X8/__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/hinge.culabels are not correctly providedinfo.labels.Size() != 0Ulabel set cannot be emptypreds.size=, label.size=binary:hingeHinge loss. Expects labels to be in [0,1f]N7xgboost3obj8HingeObjE*N7xgboost3objL32__make_ObjFunctionReg_HingeObj__MUlvE_ESoftmax 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 0.0f && base_score < 1.0fbase_score must be in (0,1) for logistic loss, got: /__w/ml-builds/ml-builds/xgboost/src/objective/../common/common.hInvalid shape of labels.RegLossParamscale_pos_weightPoissonRegressionParamTweedieRegressionParamtweedie_variance_powerreg:squaredlogerrorreg:logisticbinary:logisticbinary:logitrawreg:linearreg:pseudohubererrorreg:tweedieMean absoluate error.StringView{get(in["name"])} == StringView{"reg:absoluteerror"}PoissonRegression: label must be nonnegativeGammaRegression: label must be positive.TweedieRegression: label must be nonnegativepseudo_huber_paramtweedie_regression_parampoisson_regression_paramt_v.Shape(1) != 0Sum of weights is close to 0.0, skipping base score estimation.Check failed: last_abs_y <= abs_yCoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed!reg_loss_paramlabel 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_11LogisticRawEEEN7xgboost3obj21PseudoHuberRegressionEN7xgboost3obj17PoissonRegressionEN7xgboost3obj13CoxRegressionEN7xgboost3obj15GammaRegressionEN7xgboost3obj17TweedieRegressionEN7xgboost3obj17MeanAbsoluteErrorE*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*N7xgboost3objL40__make_ObjFunctionReg_LinearRegression__MUlvE_E*N7xgboost3objL45__make_ObjFunctionReg_PseudoHuberRegression__MUlvE_E*N7xgboost3objL41__make_ObjFunctionReg_PoissonRegression__MUlvE_E*N7xgboost3objL37__make_ObjFunctionReg_CoxRegression__MUlvE_E*N7xgboost3objL39__make_ObjFunctionReg_GammaRegression__MUlvE_E*N7xgboost3objL41__make_ObjFunctionReg_TweedieRegression__MUlvE_E*N7xgboost3objL41__make_ObjFunctionReg_MeanAbsoluteError__MUlvE_EffBpoisson_regressitweedie_regressiư>xد 0@hXhPh/__w/ml-builds/ml-builds/xgboost/src/predictor/../data/proxy_dmatrix.h/__w/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.ccbase_margin.Shape(1) == ngroup/__w/ml-builds/ml-builds/xgboost/src/predictor/../common/threading_utils.hmodel.param.size_leaf_vector == 0size_leaf_vector is enforced to 0 so farT<llP0 tdTD$4hH($Dl\|DpP0@ncolumns != 0m->NumColumns() == model.learner_model_param->num_featureNumber of columns in data must equal to trained model.Inplace predict accepts only DMatrixProxy as input.out_preds->size() == p_fmat->Info().num_row_ * model.learner_model_param->num_output_groupMake predictions using CPU.N7xgboost9predictor12CPUPredictorESt10shared_ptrIN7xgboost4data12DenseAdapterEESt10shared_ptrIN7xgboost4data10CSRAdapterEE*N7xgboost9predictorL34__make_PredictorReg_CPUPredictor__MUlPKNS_16GenericParameterEE_E?Unknown predictor type _Map_base::at[Internal error]: DMatrix: has expired./__w/ml-builds/ml-builds/xgboost/src/predictor/predictor.ccCheck failed: container_.find(m) != container_.cend()Check failed: container_.at(m).ref.lock()model.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/param.ccFound floating point number in interaction constraintsUnknown value type for interaction constraint:std::floor(d) == dK/__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: !HasCategoricalSplit()Please use JSON/UBJSON for saving models with categorical splits.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() == param.num_nodesthis->GetSplitCategoriesPtr().size() == param.num_nodesget(out["tree_param"]["num_nodes"]) == std::to_string(param.num_nodes)static_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()categories_segmentscategories_sizescategories_nodesunique_path[i].pweight == 0Unique path must have zero weightUnknown Model Builder:GraphvizParamTreeParamtree_paramsplit_indicessplit_typeloss_changessum_hessianbase_weightsleft_childrenright_childrenparentssplit_conditionsdefault_leftdot 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::nposbasic_string::replaceCheck failed: is_categoricalUnknown feature map type. in feature map is numerical but tree node is categorical.::max()number of nodes in the tree exceed 2^31ch == '{', Expect '{' but get 'j_end - j_begin != 0std::numeric_limits::min() != max_catyes_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_deletedNumber of features used in tree construction.Size of leaf vector, reserved for vector treemin_split_lossmax_depthmax_leavesgrow_policydepthwiselossguidemax_cat_to_onehotmax_cat_thresholdmin_child_weightreg_lambdareg_alphasubsamplesampling_methodgradient_basedcolsample_bynodecolsample_bylevelcolsample_bytreesketch_ratiocache_optrefresh_leafmonotone_constraintsinteraction_constraintssparse_thresholddoubleMinimum 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} {left} {right}{parent}{left}{parent}{stat} {left} {right}{stat},gain={loss_chg},cover={sum_hess}, "gain": {loss_chg}, "cover": {sum_hess} {nid} [ label="leaf={leaf-value}" {params}] {nid}{leaf-value}digraph { graph [ rankdir={rankdir} ] {graph_attrs} {nodes}}{graph_attrs}{newline}{indent}{nodes}{newline}{indent}{ "nodeid": {nid}, "leaf": {leaf} {stat}}, "cover": {sum_hess} {leaf}{sum_hess}{nid}:[{fname}] yes={yes},no={no}{fname}{yes}{no}, missingyesno{child}{color}{branch} {nid} -> {child} [label="{branch}" color="{color}"] {tabs}{nid}:leaf={leaf}{stats},cover={cover}{tabs}{stats}{nodes} {nid} [ label="{fname}:{cond}" {params}] {cond}{params} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "yes": {yes}, "no": {no}{depth}{missing}{tabs}{nid}:[{fname}<{cond}] yes={left},no={right},missing={missing}{tabs}{nid}:[{fname}:{cond}] yes={right},no={left},missing={missing}{tabs}{nid}:[f{fname}<{cond}] yes={left},no={right},missing={missing}{{properties} {stat}, "children": [{left}, {right} {indent}]}{properties} "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="{fname}{<}{cond}" {params}] n_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_nodesn_nodes == split_categories_segments.size()" 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_EHgY?@חA??Unknown tree updater /__w/ml-builds/ml-builds/xgboost/src/tree/tree_updater.ccupper_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/hist_util.hid != kMax/__w/ml-builds/ml-builds/xgboost/src/tree/../data/../common/threading_utils.hi < ranges_.size()i < first_dimension_.size()end > beginnid < nodes_/__w/ml-builds/ml-builds/xgboost/src/tree/../common/partition_builder.hCheck failed: tree[node.node_id].IsLeaf()ptr_offset <= row_set.Data()->size()/__w/ml-builds/ml-builds/xgboost/src/tree/../data/proxy_dmatrix.hbegin < end/__w/ml-builds/ml-builds/xgboost/src/tree/../data/../common/row_set.hbegin + n_left + n_right == e.endn_left == 0n_right == 0n_left + n_right == e.Size()begin + n_left <= e.end/__w/ml-builds/ml-builds/xgboost/src/tree/common_row_partitioner.h(*p_tree)[nid].LeftChild() + 1 == (*p_tree)[nid].RightChild()row_ptr_[nid] == kMaxtid < nthreads_nthreads >= 1elem_of_each_node_.size() == 0UInitData/__w/ml-builds/ml-builds/xgboost/src/tree/updater_approx.ccn_total_bins == page.cut.TotalBins()/__w/ml-builds/ml-builds/xgboost/src/tree/hist/histogram.h/__w/ml-builds/ml-builds/xgboost/src/tree/hist/evaluate_splits.hout_preds.DeviceIdx() == GenericParameter::kCpuIdout_preds.Size() > 0UCheck failed: p_last_treepart.Size() == n_nodesout_preds.Size() == data->Info().num_row_UpdatePredictionCachecut_ptr[fidx] <= static_cast(std::numeric_limits::max())cut_ptr[fidx + 1] <= static_cast(std::numeric_limits::max())partition > 0Check failed: !features.empty()nodes == targeted_hists.size()base_rowid == gmat.base_rowidany_missing == truen_nodes > 0n_batches_ >= 1InitRoot/__w/ml-builds/ml-builds/xgboost/src/tree/hist/../../common/transform.hLeafPartitionCheck failed: param.sampling_method != TrainParam::kGradientBasedGradient based sampling is not supported for approx tree method.FbRKN7xgboost4tree14CPUExpandEntryES3_EN7xgboost11TreeUpdaterEN7xgboost4tree19GlobalApproxUpdaterEN7xgboost6common6ColumnIhEEN7xgboost6common16SparseColumnIterIhEE*N7xgboost4treeL39__make_TreeUpdaterReg_GlobalHistMaker__MUlPKNS_16GenericParameterENS_7ObjInfoEE_EPFbRKN7xgboost4tree14CPUExpandEntryES3_EN7xgboost6common6ColumnItEEN7xgboost6common16SparseColumnIterItEEN7xgboost6common6ColumnIjEEN7xgboost6common16SparseColumnIterIjEESt23_Sp_counted_ptr_inplaceIN7xgboost6common13ColumnSamplerESaIS2_ELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost6common16PartitionBuilderILm2048EE9BlockInfoELN9__gnu_cxx12_Lock_policyE2EEUpdatePredictionGlobalApproxUpdagrow_colmakerGrow tree with parallelization over columns.ColMakerTrainParam/__w/ml-builds/ml-builds/xgboost/src/tree/updater_colmaker.ccCheck failed: this->ctx_/__w/ml-builds/ml-builds/xgboost/src/tree/../common/threading_utils.hridx < position_.size()ridx exceed bound ridx= pos=Check 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.param_.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.N7xgboost4tree8ColMaker7BuilderEN7xgboost4tree8ColMakerE*N7xgboost4treeL32__make_TreeUpdaterReg_ColMaker__MUlPKNS_16GenericParameterENS_7ObjInfoEE_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_16GenericParameterENS_7ObjInfoEE_E/src/tree/update/__w/ml-builds/ml-builds/xgboost/src/tree/./updater_quantile_hist.h/__w/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.cc/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/histogram.hGrow tree using quantized histogram./__w/ml-builds/ml-builds/xgboost/src/tree/./hist/../../common/hist_util.h/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/../../common/threading_utils.hexponent <= modrow_ptr.size() >= 2EvaluateSplitsExpandTreeQuantile::Builder/__w/ml-builds/ml-builds/xgboost/src/tree/./../common/partition_builder.h/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/../../data/proxy_dmatrix.h/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/../../common/row_set.h/__w/ml-builds/ml-builds/xgboost/src/tree/./common_row_partitioner.h/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/evaluate_splits.h/__w/ml-builds/ml-builds/xgboost/src/tree/./hist/../../common/transform.hN7xgboost4tree17QuantileHistMakerE*N7xgboost4treeL41__make_TreeUpdaterReg_QuantileHistMaker__MUlPKNS_16GenericParameterENS_7ObjInfoEE_E::max()Refresher that refreshes the weight and statistics according to data.N7xgboost4tree13TreeRefresherE*N7xgboost4treeL37__make_TreeUpdaterReg_TreeRefresher__MUlPKNS_16GenericParameterENS_7ObjInfoEE_EsyncSyncher that synchronize the tree in all distributed nodes.N7xgboost4tree11TreeSyncherE*N7xgboost4treeL35__make_TreeUpdaterReg_TreeSyncher__MUlPKNS_16GenericParameterENS_7ObjInfoEE_E/__w/ml-builds/ml-builds/xgboost/rabit/src/allreduce_base.ccrabit_reduce_ring_mincount should be greater than 0invalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB}rabit_timeout_sec should be non negative second Retry connecting to IP(retry time: tracker.SendAll(&magic, sizeof(magic)) == sizeof(magic)tracker.RecvAll(&magic, sizeof(magic)) == sizeof(magic)sync::Invalid tracker message, init failuretracker.Send(xgboost::StringView{task_id}) == task_id.size()must keep rank to same if the node already have onetracker got overwhelmed and not able to assign correct rankbind(handle_, handle, sizeof(std::remove_reference_t))getsockname(handle_, reinterpret_cast(&res_addr), &addrlen)ReConnectLink fail to bind the ports specifiedgetsockopt(handle_, SOL_SOCKET, SO_ERROR, reinterpret_cast(&error), &len)ReConnectLink failure, link rank inconsistentOverride a link that is activesetsockopt(handle_, SOL_SOCKET, SO_KEEPALIVE, reinterpret_cast(&keepalive), sizeof(keepalive))setsockopt(handle_, IPPROTO_TCP, TCP_NODELAY, reinterpret_cast(&tcp_no_delay), sizeof(tcp_no_delay))cannot find parent in the linkcannot find prev ring in the linkcannot find next ring in the linkhadoop_mode is set but cannot find mapred_task_idhadoop_mode is set but cannot find mapred_map_tasksRabit Module currently only work with dmlc workergethostname(&buf[0], HOST_NAME_MAX)too large type_nbytes=%lu, buffer_size=%luReadToRingBuffer: buffer not allocatedReadToRingBuffer: max_size_read checkBroadcast: root should be smaller than world sizerabit_tracker_urirabit_tracker_portrabit_task_idDMLC_TRACKER_URIDMLC_TRACKER_PORTDMLC_TASK_IDDMLC_ROLErabit_world_sizerabit_hadoop_moderabit_tree_reduce_minsizerabit_reduce_ring_mincountrabit_reduce_buffer%lu%cinvalid format for %sDMLC_WORKER_CONNECT_RETRYrabit_bootstrap_cacherabit_debugrabit_timeoutrabit_timeout_secrabit_enable_tcp_no_delayConnecting to (failed): [] ReConnectLink failure 3printshutdownFailed to shutdown due totask connected to the trackerReConnectLink failure 4 got new rank listen(handle_, backlog)ReConnectLink failure 5ReConnectLink failure 6ReConnectLink failure 7ReConnectLink failure 8ReConnectLink failure 9ReConnectLink failure 10ReConnectLink failure 12ReConnectLink failure 13ReConnectLink failure 14acceptReConnectLink failure 15ReConnectLink: bad socketfcntlfailed in ReconnectLink mapred_tip_id%[^=]=%smapreduce_task_idmapred_task_id%drabit_num_trialmapred_map_tasksmapreduce_job_mapsworkercan only call Init oncestart256MBDMLC_NUM_ATTEMPTneed to assume rank structurewrite ptr boundary checkAllreduce: boundary check[%d] read_ptr boundary checkbuffer size inconsistentmust assign buffer_sizeAllreduce: size checkAllreduce: boundary errorPoll timeoutFailed to poll./__w/ml-builds/ml-builds/xgboost/rabit/include/rabit/internal/socket.hAllgatherRing failedAllreduce failedBroadcast failedN5rabit6engine7IEngineEN5rabit6engine13AllreduceBaseE/rabit/src/allreDMLC_NUM_ATTEMPTDMLC_TRACKER_URIDMLC_TRACKER_PORDMLC_WORKER_CONNunknown data_typeFailed to initialize RABIT.unknown enum_ophh(((Failed to shutdown RABIT worker. 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()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() == 1ulN4dmlc2io23IndexedRecordIOSplitterEL$d</__w/ml-builds/ml-builds/xgboost/dmlc-core/src/io/input_split_base.ccCheck failed: offset_end_ >file_offset_[file_ptr_end_]Check failed: file_ptr_end_ < files_.size()file offset not calculated correctlyThis could due to compiler version, g++-4.9 is neededCannot find any files that matches the URI pattern Check failed: files_[i].size % align_bytes == 0Unexpected end of regex when escaping.Unexpected end of regex when reading control code.Unexpected end of regex when ascii character.curr=,begin=,end=,fileptr=,fileoffset=offset[]= bad regex files_.size() != 0Ufile do not align by bytesNULSOHSTXETXEOTENQACKalertbackspacenewlinevertical-tabform-feedcarriage-returnSOSIDLEDC1DC2DC3DC4NAKSYNETBCANEMSUBESCIS4IS3IS2IS1exclamation-markquotation-marknumber-signdollar-signpercent-signampersandapostropheleft-parenthesisright-parenthesisasteriskplus-signcommahyphenperiodonetwothreefourfivesixsevenninesemicolonless-than-signequals-signgreater-than-signquestion-markcommercial-atAGJPSVWZleft-square-bracketbackslashright-square-bracketcircumflexunderscoregrave-accentuzleft-curly-bracketvertical-lineright-curly-brackettildeDELalnumblankcntrlgraphlowerpunctupperxdigitUnexpected escape character.Unexpected end of regex when in an open parenthesis.Invalid special open parenthesis.Unexpected end of regex when in brace expression.Unexpected character in brace expression.Unexpected end of character class.Unexpected end of regex when in bracket expression.Unexpected character class open bracket.^$\.*+?()[]{}|.[\()*+?{|^$.[\*^$.[\()*+?{|^$ .[\*^$ 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.Яr]ЯGЯЯЯ9ЯЯЯ'ЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯЯtaLt6ttt&ttttttttttttttttttttttttttttttttttttttttttttttttttttҰ8`888888888888888888888888888888888888888888888888888888888ZzfUD1 ! 444444444444444444444444444444444444444444444444444444444 s a P|T, 8hpPxT4Invalid character class.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.Invalid range in bracket expression.Character is expected after a dash.Unexpected character in bracket expression.Parenthesis is not closed.N4dmlc2io14InputSplitBaseESt23_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_traitsIcEELb1ELb1EEEwwstdoutwbCheck failed: allow_null LocalFileSystem::Open "": error: 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 N4dmlc2io10FileSystemE;x8(姴?Tdip˱* \/컴x,\98JôŴ$mǴɴʴL2̴ʹnϴѴ{ҴxӴXմ`ִ?شPٴF۴ܴݴߴxaT$Nh<)`HOp*,SuLUXGDj,  x$X $x{<]#&'* $-'.@0`2D56 j9l@CUGJDnJ& K'=K'}K(L@)N),PH*.P*0P,`Q.Q/R1Sx2T2U3V7 W8[h=<\A\I\HQ]<]L]J],k]|]^P` 0` P`t`̙`` adaLcԜd\ dȝZd|dde&elef|ffdfأfLfĤ(g*g,Pz>zh@zpBzB{C {C{(D\|D}E~(Jc4`d^PB@2hp\8p8DܻHx :xNT  |   l \xkWDt||& 8`d$d\ (#Jp#|$(D)# 0f 1 P2 2 h3@!3p!6!8!8" 9R"d9"9"9#D~#H#L#( {`({(}(ȂX)w)|+xB+̤a+,,c-T.Q/N0 K1H2934 647D7 77<778X8899H5:.;L[;p;;4;;;;d;<|'O<<><>=L@L=@=A8>pA>A>IBlJBLCDCvCC`D@vDDDDE(3G@RGBHaHHIIlJ<`KKL$*MTOOO(RP~P(PP@&QQQ RVXVV8VW\ XT X Yx!Y"Y\'Z+P[lT[xf[f\i7\Pmx\m\\o]q]u^vl_x_x_y4`z`{`X|`a|c}cggDh|Dldlp2mЃtmm,m0*n\n0n(oPo rP`rȕ"ty8zzP {b{|t||,~ܠ<[l恶p&z΂8tNΆX ~.8>N x&''l(.P+P+B0,ƕ$-k4ʗ56. 77d8LE^pVܜV̝dWXYҞpZ~[`L\Hx&)أ +-8`-h,QlȤt(X8&ȥ4=8H>hB ?lxAxC@xEG(xIJLhNOtHRS`WZ8\h\\,x](^_8haxd`g8ili`l}PX؅pX|(h(x<$(ŷʷ (Ϸ4ӷ׷$۷`x8X@h X(hX8%PX]kxr@rlrrss(s8sHsXs hs xs4sHs\spssssstt(t8t$Ht8XtLht`xttttttttttu(u<8uPHudhuxxuuuuuuv(v8v,Xv@hvTvhv|vvvw(wHwXwxw$w8wLw`wtwxx(x8xHxXxhxxx(x<xPxdxxxxxxyy(y8yHy,Xy@hyTxyhy|(zzz8{ {h{|{|8||dh0H؀h؃\xTX<XhHhxȾX$(øĸhŸŸǸ8hȸ(ɸɸH˸˸Th̸̸H͸͸и`8Ҹָ8ڸ\hݸ(LH,X@X$T|xXP lX pX"'L0H380=BL Sd hW Z _\ 8c 8u zP } 肹| 8 茹 l H ؗ(ؠ(0حdH`H˹HԹ۹(xDxX$#x8%'t/,h<OLP(QQQ#R&R$&V&XW hW, xW@ WT Wh W| W hY [ ^ ` Xb 8f!g!i0!lD!nX!8pl!xs!(u!v!y!{!8}!8! 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