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distributed mode detected, will split data among workers/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/c_api/c_api.ccCheck failed: mat.info.num_col_ <= num_col: num_col= vs mat.info.num_row_ <= num_rowmat.info.num_row_ == offset_vec.size() - 1Check failed: nan_missingThere are NAN in the matrix, however, you did not set missing=NANCheck failed: !badnan[i]float32float64bool8int32int8int16int64Unknown data table type.DMatrix/Booster has not been intialized or has already been disposed.src.info.group_ptr_.size() == 0Uslice does not support group structureCheck failed: iter->Next()static_cast(ridx) < batch.Size()labelweightbase_marginUnknown float field name root_indexUnknown uint field name rwtextallocator::allocate(size_t n) 'n' exceeds maximum supported sizeCheck failed: at_first_cannot reset NativeDataIter[] :%02d:%02d:%02d Stack trace: [bt] () _Z/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/common/span.hCheck failed: _count >= 0Check failed: _ptr || _count == 0eval_metricSAVED_PARAM_Check failed: learner_->GetAttr(attr_name, &saved_param_value)read can not have position excceed buffer lengthAssertError:%s write position exceed fixed buffer size/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./feature_map.hfid == static_cast(names_.size()) ( vs. iqintfloatunknown feature type, use i for indicator and q for quantityHistCutMatrix/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/common/hist_util.ccRow does not lie in any group! nthread == omp_get_num_threads()summary_array.size() == in_sketchs->size()cut.size() <= std::numeric_limits::max()cut_size > row_ptr.back()Check failed: cbegin != cendcut.cut.size() > 0Uibegin + inst.size() == iend======== Monitor: ========/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/common/./timer.hTimer for did not get stopped properly.s, calls @ us/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/data.hCheck failed: impl_ != nullptr/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/common/span.h/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/common/./quantile.hinvalid init parameterCheck failed: nlevel <= limit_size * epsCheck failed: 0 <= index_ && index_ != span_->size()Check failed: index_ < span_->size()mingap=, maxgap=, wgap=Check failed: size <= sa.size + sb.sizebug in combinefi.Read(&this->size, sizeof(this->size)) == sizeof(this->size)fi.Read(this->data, this->size * sizeof(Entry)) == this->size * sizeof(Entry) check quantile stats, nbig=, n= srcsize=, maxsize=, range=, chunk=Check failed: nbig < nquantile: too many large chunk] rmin=, rmax=, wmin=, v=/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/common/host_device_vector.ccSize() == other.Size()Size() == other.size()/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/data.ccCheck failed: fi->Read(&version, sizeof(version)) == sizeof(version)MetaInfo: invalid versionCheck failed: version >= 1 && version <= kVersionMetaInfo: unsupported file versionCheck failed: fi->Read(&num_row_, sizeof(num_row_)) == sizeof(num_row_)MetaInfo: invalid formatCheck failed: fi->Read(&num_col_, sizeof(num_col_)) == sizeof(num_col_)Check failed: fi->Read(&num_nonzero_, sizeof(num_nonzero_)) == sizeof(num_nonzero_)Check failed: fi->Read(&labels_.HostVector())Check failed: fi->Read(&group_ptr_)Check failed: fi->Read(&qids_)Check failed: fi->Read(&weights_.HostVector())Check failed: fi->Read(&root_index_)Check failed: fi->Read(&base_margin_.HostVector())Unknown data typegroupcache_file.find('#') == std::string::nposOnly one `#` is allowed in file path for cache file specification..r-XGBOOST_TEST_NPARTLoad part of data of partsauto matrix with entries loaded from .group groups are loaded from .base_margin base_margin are loaded from .weight weights are loaded from .row.pageUnknown format type rawCheck failed: batch.index != nullptroffset_vec.back() == data.Size()self_offset.size() == other_offset.size()self_data.size(): , other_data.size(): beg < data.size()ptr < offset.size()/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/../common/io.hNot implementedInvalid Parameter format for expect but value=' optional, default=, requiredRequired parameter is not presentedvalue for Parameter exceed bound [ should be greater equal to should be smaller equal to optional, default='/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/./parameter.henum_back_map_.count(value) != 0UValue not found in enum declaredmap::at: key not foundInvalid Input: '', valid values are: /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/simple_csr_source.ccCheck failed: info.qids_.empty() || info.qids_.size() == info.num_row_Check failed: fi->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic)invalid input file formattmagic == kMagicinvalid format, magic number mismatch/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/simple_dmatrix.ccCheck failed: page_ != nullptrCheck failed: _idx >= 0 && _idx < size().sorted.col.page.col.page/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_dmatrix.ccCheck failed: source_ != nullptrRaw binary data format./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_raw_format.ccpage->offset.Size() != 0UInvalid SparsePage filefi->Read(dmlc::BeginPtr(data_vec), (page->data).Size() * sizeof(Entry)) == (page->data).Size() * sizeof(Entry)fid + 1 < disk_offset_.size()disk_offset_[fid] > curr_offsetfi->Read(dmlc::BeginPtr(data_vec) + offset_vec[i], size_to_read * sizeof(Entry)) == size_to_read * sizeof(Entry)Check failed: page.offset.Size() != 0 && offset_vec[0] == 0offset_vec.back() == page.data.Size()/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_source.cccache_shards.size() != 0Ufinfo->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic)Check failed: fi->Read(&format)Invalid page formatWriting to in MB/s, writtenSparsePageSource::CreateRowPage Finished writing to Unknown page type: Writing to SparsePageSource: Finished writing to /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/threadediter.hCheck failed: !producer_sig_processed_unique_lock::unlock: not lockedCheck failed: out_data_ != NULLCalling Value at beginning or end?thread constructor failedCheck failed: producer_sig_ == kDestroyCheck failed: cell != __null || produce_end_.load(std::memory_order_acquire)Check failed: producer_sig_ != kDestroyCheck failed: producer_sig_ == kProduceMake sure you call BeforeFirst not inconcurrent with Next!Check failed: produce_end_.load(std::memory_order_acquire)/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_writer.ccname_shards.size() == format_shards.size()Check failed: *out_page == nullptrCheck failed: qrecycle_.Pop(out_page)SparsePage::Writer Finished writing to GBLinearModelParamGBLinearTrainParamLinear booster, implement generalized linear model.num_featureNumber of features used in classification.num_output_groupNumber of output groups in the setting.int (non-negative)/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/parameter.hkey has already been registered in updatershotgunUpdate algorithm for linear model. One of shotgun/coord_descenttoleranceStop if largest weight update is smaller than this number.max_row_perbatchMaximum rows per batch.stringOut of range value for , value='pos <= value.length()Some trailing characters could not be parsed: 'Out of range valueNo conversion could be performed/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h*p == ')'Invalid NAN literal/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/../common/timer.h__Cannot find argument '', Possible Arguments: ---------------- : /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/gbm/gblinear_model.hfi->Read(¶m, sizeof(param)) == sizeof(param)DoBoostPredictBatchInternal/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./data.hPredictBatch/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/gblinear.ccntree_limit == 0UGBLinear::Predict ntrees is only valid for gbtree predictorgblinear does not support prediction of leaf indexGBLinear::PredictContribution: ntrees is only valid for gbtree predictorjson { "bias": [, ], "weight": [ ] }bias: weight: /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/gbm.ccUnknown gbm type GBTreeModelParamGBTreeTrainParamDartTrainParamgbtreeTree booster, gradient boosted trees.Tree booster, dart.Number of output groups to be predicted, used for multi-class classification.num_rootsTree updater sequence.Number of features used for training and prediction.size_leaf_vectorReserved option for vector tree.num_parallel_treeNumber of parallel trees constructed during each iteration. This option is used to support boosted random forest.updater_seqgrow_colmaker,pruneprocess_typedefaultupdateWhether to run the normal boosting process that creates new trees, or to update the trees in an existing model.predictorcpu_predictorPredictor algorithm typeEnum ( exisit!) Enums: ), has not been registered in Alias sample_typeuniformDifferent types of sampling algorithm.normalize_typeforestDifferent types of normalization algorithm.rate_dropFraction of trees to drop during the dropout.Whether at least one tree should always be dropped during the dropout.skip_dropProbability of skipping the dropout during a boosting iteration.learning_rateLearning rate(step size) of update.etatruefalse10booleanGBTree/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/gbm/gbtree_model.hGBTree: invalid model filefi->Read(dmlc::BeginPtr(tree_info), sizeof(int) * param.num_trees) == sizeof(int) * param.num_trees/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/tree_model.hfi->Read(¶m, sizeof(TreeParam)) == sizeof(TreeParam)param.num_nodes != 0fi->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_deletedparam.num_trees == static_cast(trees.size())param.num_nodes == static_cast(nodes_.size())param.num_nodes == static_cast(stats_.size())distcolBoostNewTrees/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/gbtree.ccin_gpair->Size() % ngroup == 0Umust have exactly ngroup*nrow gpairsCommitModelmodel_.trees.size() < model_.trees_to_update.size()out_preds->size() == nnum_group == model_.param.num_output_groupmodel_.param.size_leaf_vector == 0size_leaf_vector is enforced to 0 so farpreds.size() == p_fmat->Info().num_row_ * num_groupdrop trees, weight = LearnerModelParamLearnerTrainParamreg:squarederror/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/./common/timer.hbs64/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/learner.ccheader != "bs64"Base64 format is no longer supported in brick.binffp.Read(&header[0], 4) == 4Ufi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_)BoostLearner: wrong model formatfi->Read(&len, sizeof(len)) == sizeof(len)fi->Read(&gap, sizeof(gap)) == sizeof(gap)fi->Read(&name_obj_[0], len) == lenCheck failed: fi->Read(&name_gbm_)gpu_predictorParameter 'predictor' will be set to 'cpu_predictor' since XGBoost wasn't compiled with GPU support.count:poissonmax_delta_stepnum_class/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/./common/io.hcount_poisson_max_delta_stepn_gpusgpu_id0.7Learnerobjectivemulti:softmaxboosterdartDANGER 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.grow_histmaker,pruneTree method is selected to be 'hist', which uses a single updater grow_quantile_histmaker.grow_quantile_histmakergrow_gpu,prunegrow_gpu_histUnknown tree_method () detectedXGBoost version not compiled with GPU support.Check failed: matrix != nullptrnum_col <= static_cast(std::numeric_limits::max())Unfortunately, XGBoost does not support data matrices with features or greatermparam_.num_feature != 00 feature is supplied. Are you using raw Booster interface?Check failed: obj_ == nullptr && gbm_ == nullptrUpdateOneIterCheck failed: ModelInitialized()Always call InitModel or LoadModel before updatePredictRawGetGradientCheck failed: weights.size() == info.group_ptr_.size() - 1weights size: groups size: num rows: Number of weights should be equal to number of groups in ranking task.Check failed: tparam_.dsplit != DataSplitMode::kAutoPrecondition violated; dsplit cannot be 'auto' in distributed modeColumn-wise data split is currently not supported.Tree method is automatically selected to be 'approx' for distributed training.Tree method was set to be exact', but only 'approx' and 'hist' is available for distributed training. The `tree_method` parameter is now being changed to 'approx'Distributed training is not available with GPU algoritmsTree method is specified to be 'hist' for distributed training.Tree method is automatically set to 'approx' since external-memory data matrix is used.Tree method was set to be 'exact', but currently we are only able to proceed with approximate algorithm ('approx') because external-memory data matrix is used.External-memory data matrix is not available with GPU algorithmsTree 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: gbm_ != nullptrPredict must happen after Load or InitModelBoostOneIterAlways call InitModel or LoadModel before boost.EvalOneIterbase_scoreGlobal bias of the model.Number of features in training data, this parameter will be automatically detected by learner.Number of class option for multi-class classifier. By default equals 0 and corresponds to binary classifier.Random number seed during training.seed_per_iterationSeed PRNG determnisticly via iterator number, this option will be switched on automatically on distributed mode.dsplitcolrowData split mode for distributed training.tree_methodapproxgpu_exactChoice of tree construction method.test_flagInternal test flagnthreadNumber of threads to use.disable_default_eval_metricflag to disable default metric. Set to >0 to disable/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/linear/linear_updater.ccUnknown linear updater LinearTrainParamLearning rate of each update.reg_lambdaL2 regularization on weights.reg_alphaL1 regularization on weights.feature_selectorcyclicshufflethriftygreedyrandomFeature selection or ordering method.Number of devices to use.Primary device ordinal.lambdaalphaCoordinateParamcoord_descentUpdate linear model according to coordinate descent algorithm.top_kThe number of top features to select in 'thrifty' feature_selector. The value of zero means using all the features./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/linear/../common/timer.hCoordinateUpdater/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/linear/coordinate_common.hunknown coordinate selector: UpdateFeatureUpdate linear model according to shotgun coordinate descent algorithm./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/linear/updater_shotgun.ccUnsupported feature selector for shotgun updater. Supported options are: {cyclic, shuffle}ConsoleLoggerParamWARNING: DEBUG: INFO: silentDo not print information during training.verbosityFlag to print out detailed breakdown of runtime.debug_verbosermseRooted mean square error.maeMean absolute error.loglossNegative loglikelihood for logistic regression.poisson-nloglikNegative loglikelihood for poisson regression.gamma-devianceResidual deviance for gamma regression.gamma-nloglikNegative log-likelihood for gamma regression.errorBinary classification error.tweedie-nlogliktweedie-nloglik@rho for tweedie regression./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/metric/elementwise_metric.cuinfo.labels_.Size() != 0Ulabel set cannot be emptypreds.Size() == info.labels_.Size()label and prediction size not match, hint: use merror or mlogloss for multi-class classification/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/common/common.hgpu_id >= 0gpu_id must be >= 0.n_gpus >= -1n_gpus must be >= -1.Check failed: gpu_id < n_devices_visible gpu_id should be less than number of visible devices. gpu_id: , number of visible devices: n_gpus <= n_available_devicesStarting from gpu id: , there are only available devices, while n_gpus is set to: %fsscanf(param, "%f", &threshold_) == 1unable to parse the threshold value for the error metricCheck 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@/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/metric/metric.ccUnknown metric function MetricParamNumber of GPUs to use for multi-gpu algorithms.gpu to use for objective function evaluationmerrorMulticlass classification error.mloglossMulticlass negative loglikelihood./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/metric/multiclass_metric.cuCheck failed: preds.Size() % info.labels_.Size() == 0label and prediction size not matchnclass >= 1Umlogloss and merror are only used for multi-class classification, use logloss for binary classificationCheck failed: label_error >= 0 && label_error < static_cast(n_class)MultiClassEvaluation: label must be in [0, num_class), num_class= but found in labelamsAMS metric for higgs.aucArea under curve for both classification and rank.aucprArea under PR curve for both classification and rank.preprecision@k for rank.ndcgndcg@k for rank.mapmap@k for rank.cox-nloglikNegative log partial likelihood of Cox proportioanl hazards model./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/metric/rank_metric.ccAMS must be in format ams@kams@Check failed: !distributedmetric AMS do not support distributed evaluationbest-ams-ratio=label size predict size not matchgptr.back() == info.labels_.Size()EvalAuc: group structure must match number of predictionCheck failed: !auc_errorAUC: the dataset only contains pos or neg samplesEvalAucPR: group structure must match number of predictionAUC-PR: error in calculationAUC-PR: the dataset only contains pos or neg samplesdat[0] <= dat[1]AUC-PR: AUC > 1.0sum_auc <= static_cast(ngroup)%u[-]?gptr.size() != 0Umust specify group when constructing rank filegptr.back() == preds.Size()EvalRanklist: group structure must match number of predictionCox metric does not support distributed evaluationHingeObjParambinary:hingeHinge loss. Expects labels to be in [0,1f]/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/objective/hinge.culabels are not correctly providedpreds.size=, label.size=/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/objective/../common/transform.hNot part of device code. WITH_CUDA: SoftmaxMultiClassParamSoftmax for multi-class classification, output class index.multi:softprobSoftmax for multi-class classification, output probability distribution.Number of output class in the multi-class classification./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-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 matchSoftmaxMultiClassObj: label must be in [0, num_class).Check failed: _offset >= 0 && (_offset < size() || size() == 0)Check failed: (_count == dynamic_extent) || (_count >= 0 && _offset + _count <= size())Check failed: (index_ + n) >= 0 && (index_ + n) <= span_->size()Check failed: span_ == rhs.span_/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/objective/objective.ccObjective candidate: Unknown objective function LambdaRankParamrank:pairwisePairwise rank objective.rank:ndcgLambdaRank with NDCG as objective.LambdaRank with MAP as objective.num_pairsampleNumber of pair generated for each instance.fix_list_weightNormalize the weight of each list by this value, if equals 0, no effect will happen/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/objective/rank_obj.ccCheck failed: gptr.size() != 0 && gptr.back() == info.labels_.Size()group structure not consistent with #rowsRegLossParamRegression with squared error.reg:logisticLogistic regression for probability regression task.binary:logisticLogistic regression for binary classification task.binary:logitrawLogistic regression for classification, output score before logistic transformation.reg:lineargpu:reg:linearDeprecated. Linear regression (computed on GPU).gpu:reg:logisticDeprecated. Logistic regression for probability regression task (computed on GPU).gpu:binary:logisticDeprecated. Logistic regression for binary classification task (computed on GPU).gpu:binary:logitrawDeprecated. Logistic regression for classification, output score before logistic transformation (computed on GPU)PoissonRegressionParamPossion regression for count data.survival:coxCox regression for censored survival data (negative labels are considered censored).GammaRegressionParamreg:gammaGamma regression for severity data.TweedieRegressionParamreg:tweedieTweedie regression for insurance data.scale_pos_weightScale the weight of positive examples by this factor/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/objective/regression_obj.culabel must be in [0,1] for logistic regression/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/objective/./regression_loss.hCheck failed: base_score > 0.0f && base_score < 1.0fbase_score must be in (0,1) for logistic lossreg:linear is now deprecated in favor of reg:squarederror.gpu:reg:linear is now deprecated, use reg:linear instead.gpu:reg:logistic is now deprecated, use reg:logistic instead.gpu:binary:logistic is now deprecated, use binary:logistic instead.gpu:binary:logitraw is now deprecated, use binary:logitraw instead.Maximum delta step we allow each weight estimation to be. This parameter is required for possion regression.PoissonRegression: label must be nonnegativeCheck failed: last_abs_y <= abs_yCoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed!GammaRegression: label must be nonnegativetweedie_variance_powerTweedie variance power. Must be between in range [1, 2).TweedieRegression: label must be nonnegativeMake predictions using CPU./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/predictor/cpu_predictor.ccout_preds->Size() == nWarning: Ignoring the base margin, since it has incorrect length. The base margin must be an array of length [num_class] * [number of data points], i.e. * = . [number of data points], i.e. Instead, all data points will use base_score = model.param.size_leaf_vector == 0/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/predictor/predictor.ccUnknown predictor type /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/split_evaluator.ccUnknown SplitEvaluator ElasticNetParamselastic_netUse an elastic net regulariserMonotonicConstraintParamsmonotonicEnforces that the tree is monotonically increasing/decreasing w.r.t. specified featuresInteractionConstraintParamsinteractionEnforces interaction constraints on tree featuresL2 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 constraintElasticNet does not accept an inner SplitEvaluatormonotone_constraintsConstraint of variable monotonicityMonotonicConstraint must be given an inner evaluatorCheck failed: !std::isnan(mid)Check failed: nodeid < upper_.size()interaction_constraintsConstraints for interaction representing permitted interactions.The constraints must be specified in the form of a nest list,e.g. [[0, 1], [2, 3, 4]], where each inner list is a group ofindices of features that are allowed to interact with each other.See tutorial for more informationNumber of total features usedInteractionConstraint must be given an inner evaluator/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/./json.hch == '['Error at, Expect '{' but get ' Line , around ^``ch == ',', JSON array expect ']' or ','. Get '' insteadCheck failed: !is_->fail(), Expect numberTreeParamTrainParam { "nodeid": , "leaf": , "cover": }:leaf=,cover=, "depth": , "split": "", "yes": , "no": :[] yes=,no=, "split_condition": , "missing": <,missing=/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/tree_model.ccunknown fmap type, "split": :[f, "gain": ,gain=, "children": []}this->node_mean_values_.size() > 0Uunique_path[i].pweight == 0Unique path must have zero weightidx < names_.size()FeatureMap feature index exceed boundNumber of start root of trees.Number of features used in tree construction.Size of leaf vector, reserved for vector treemin_split_lossMinimum loss reduction required to make a further partition.max_depthMaximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policymax_leavesMaximum number of leaves; 0 indicates no limit.max_binif using histogram-based algorithm, maximum number of bins per featuregrow_policydepthwiselossguideTree growing policy. 0: favor splitting at nodes closest to the node, i.e. grow depth-wise. 1: favor splitting at nodes with highest loss change. (cf. LightGBM)min_child_weightMinimum sum of instance weight(hessian) needed in a child.default_directionlearnrightDefault direction choice when encountering a missing valuesubsampleRow subsample ratio of training instance.colsample_bynodeSubsample ratio of columns, resample on each node (split).colsample_bylevelSubsample ratio of columns, resample on each level.colsample_bytreeSubsample ratio of columns, resample on each tree construction.opt_dense_colEXP Param: speed optimization for dense column.sketch_epsEXP Param: Sketch accuracy of approximate algorithm.sketch_ratioEXP Param: Sketch accuracy related parameter of approximate algorithm.Size of leaf vectors, reserved for vector treesparallel_optionDifferent types of parallelization algorithm.cache_optEXP Param: Cache aware optimization.refresh_leafWhether the refresh updater needs to update leaf values.gpu to use for single gpu algorithmsNumber of GPUs to use for multi-gpu algorithms: -1=use all GPUssplit_evaluatorelastic_net,monotonic,interactionThe criteria to use for ranking splitssparse_thresholdpercentage threshold for treating a feature as sparseenable_feature_groupingif >0, enable feature grouping to ameliorate work imbalance among worker threadsmax_conflict_ratewhen grouping features, how many "conflicts" to allow.conflict is when an instance has nonzero values for two or more features.default is 0, meaning features should be strictly complementary.max_search_groupwhen grouping features, how much effort to expend to prevent singleton groups. We'll try to insert each feature into existing groups before creating a new group for that feature; to save time, only up to (max_search_group) of existing groups will be considered. If set to zero, ALL existing groups will be examined.gammadouble/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/tree_updater.ccUnknown tree updater grow_colmakerGrow tree with parallelization over columns.Distributed column split version of tree maker./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_colmaker.cctree.param.num_nodes == tree.param.num_rootsColMaker: can only grow new treefmat.Info().num_row_ == position_.size()root_index[ridx] < (unsigned)tree.param.num_roots/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/../common/random.hfeatures.size() > 0/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./tree_model.hCheck failed: node.IsLeaf()param.num_nodes < std::numeric_limits::max()number of nodes in the tree exceed 2^31ridx < position_.size()ridx exceed bound ridx= pos=prunetrees.size() == 1UDistColMaker: only support one tree at a timeCheck failed: !tree[nid].IsLeaf()inconsistent reduce informationnid >= 0grow_local_histmakerTree constructor that uses approximate histogram construction.grow_global_histmakerTree constructor that uses approximate global proposal of histogram construction.grow_histmakerTree constructor that uses approximate global of histogram construction./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/../common/quantile.h/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_histmaker.ccCheck failed: param_.max_depth > 0max_depth must be larger than 0/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/./updater_basemaker-inl.hTreeMaker: can only grow new treeroot_index[i] < (unsigned)tree.param.num_rootsroot index exceed settingnode2workindex_[nid] == static_cast(wid)summary_array_.size() == sketchs_.size()offset == -2this->wspace_.rptr.size() == (fset.size() + 1) * this->qexpand_.size() + 1fid * 2 + 1 < fminmax_.size()FeatHelper fid exceed query bound /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/./param.hret > 0UCheck failed: tree[nid].IsLeaf()sketch->temp.size < max_sizeinvalid maximum size max_size=, stemp.sizeINFO: rmax=, sum_total=, naxt_goal=, size=sketch->temp.size <= max_sizeFinalize: invalid maximum size, max_size=, stemp.size=fid * 2 < fminmax_.size()fv=, hist.size=hist[]=, hist.last=istart != hist.sizethis->qexpand_.size() == 1Uthis->wspace_.rptr.back() == this->wspace_.cut.size()Pruner that prune the tree according to statistics./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_prune.cctree pruning end, roots, extra nodes, pruned nodes, max_depth=Check failed: nodes_[nodes_[rid].LeftChild() ].IsLeaf()Check failed: nodes_[nodes_[rid].RightChild()].IsLeaf()nid >= param.num_roots/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_quantile_hist.ccGenerating gmat: secSyncHistogramsBuildLocalHistogramsBuildNodeStatsUpdateout_preds.size() > 0UCheck failed: (*p_last_tree_)[nid].IsLeaf()ColMakerHist: can only grow new treeCheck failed: (param_.max_depth > 0 || param_.max_leaves > 0)max_depth or max_leaves cannot be both 0 (unlimited); at least one should be a positive quantity.max_depth cannot be 0 (unlimited) when grow_policy is depthwise.info.root_index_.size() == 0Umin_nbins_per_feature > 0UEvaluateSplitApplySplitupper_bound < static_cast(std::numeric_limits::max())InitNewNodeCheck failed: d_step == +1 || d_step == -1cut_ptr[fid] <= static_cast(std::numeric_limits::max())cut_ptr[fid + 1] <= static_cast(std::numeric_limits::max())grow_fast_histmaker(Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram.Grow tree using quantized histogram./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/../common/column_matrix.hgmat.cut.row_ptr[fid + 1] - gmat.cut.row_ptr[fid] <= max_valQuantile::Builder/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/../common/timer.h/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/../common/hist_util.hrow_ptr_[nid] != kMaxrow_ptr_[nid] == kMaxSubtractionTrickBuildHist/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/common/row_set.hCheck failed: e.begin != nullptraccess element that is not in the setelem_of_each_node_.size() == 0Ugrow_fast_histmaker is deprecated, use grow_quantile_histmaker instead.refreshRefresher that refreshes the weight and statistics according to data./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_refresh.ccbatch.Size() < std::numeric_limits::max()grow_skmakerApproximate sketching maker./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_skmaker.ccqexpand_.size() != 0USyncher that synchronize the tree in all distributed nodes.LibSVMParserParamLibFMParserParamCSVParserParamlibsvmlibfmcsvformatFile formatindexing_modeIf >0, treat all feature indices as 1-based. If =0, treat all feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.If >0, treat all field and feature indices as 1-based. If =0, treat all field and feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.File format.label_columnColumn index (0-based) that will put into label.delimiterDelimiter used in the csv file.weight_columnColumn index that will put into instance weights./Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/disk_row_iter.hCheck failed: TryLoadCache()failed to build cache file /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/./row_block.hCheck failed: fi->Read(&label)Bad RowBlock formatCheck failed: fi->Read(&weight)Check failed: fi->Read(&qid)Check failed: fi->Read(&field)Check failed: fi->Read(&index)Check failed: fi->Read(&value)Check failed: fi->Read(&max_field, sizeof(IndexType))Check failed: fi->Read(&max_index, sizeof(IndexType))MB read, MB/secfinish reading at %g MB/secbatch.field[i] <= std::numeric_limits::max()field exceed numeric bound of current typebatch.index[i] <= std::numeric_limits::max()index exceed numeric bound of current typelabel.size() + 1 == offset.size()offset.back() == index.size()Check failed: offset.back() == value.size() || value.size() == 0/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/basic_row_iter.hfinish reading at /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data.ccUnknown data type /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/./libsvm_parser.hparam_.format == "libsvm"/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/./text_parser.hchunk.size != 0Uqid:Check failed: out->label.size() + 1 == out->offset.size()Check failed: base <= 10 && base >= 2sign == true/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/parser.hcannot call ParseNext/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/libfm_parser.hparam_.format == "libfm"Check failed: out->field.size() == out->index.size()/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/csv_parser.hparam_.format == "csv"Check failed: param_.label_column != param_.weight_column || param_.label_column < 0Must have distinct columns for labels and instance weightsDelimiter '' is not found in the line. Expected '' as the delimiter to separate fields.Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size()file://hdfs://viewfs:///Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io.ccPlease compile with DMLC_USE_HDFS=1 to use hdfss3://http://https://Please compile with DMLC_USE_S3=1 to use S3azure://Please compile with DMLC_USE_AZURE=1 to use Azureunknown filesystem protocol stdinCheck failed: part < nsplitinvalid input parameter for InputSplit::Createindexed_recordioneed to pass index file to use IndexedRecordIOrecordiounknown input split type .split.part/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/uri_spec.hname_cache.size() == 1Uonly one `#` is allowed in file path for cachefile specificationCheck failed: std::getline(is, kv.first, '=')Invalid uri argument format for key in arg Check failed: std::getline(is, kv.second) for value in arg name_args.size() == 1Urb/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/single_file_split.hCheck failed: fp_ != NULLSingleFileSplit: fail to open Check failed: part_index == 0 && num_parts == 1InputSplit do not support write:///Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/cached_input_split.hCheck failed: nread == sizeof(size) has invalid cache file formatCheck failed: fi_->Read(p->begin, size) == sizeBeforeFirst is not supportedCheck failed: this->InitCachedIter()Failed to initialize CachedIterResetPartition is not supported in CachedInputSplit/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/line_split.ccCheck failed: begin != end/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/recordio_split.ccCheck failed: fi->Read(&lrec, sizeof(lrec)) != 0invalid record io format(reinterpret_cast(begin) & 3UL) == 0U(reinterpret_cast(end) & 3UL) == 0UCheck failed: p >= pbegin + 2Check failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->endInvalid RecordIO Format(reinterpret_cast(chunk->begin) & 3UL) == 0U(reinterpret_cast(chunk->end) & 3UL) == 0UCheck failed: chunk->begin <= chunk->endCheck failed: cflag == 1UCheck failed: p[0] == RecordIOWriter::kMagic/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.ccexpanded_list.size() == 1ulIndexedRecordIOSplitter does not support multiple index files/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/input_split_base.ccCheck failed: files_[i].size % align_bytes == 0file do not align by bytesCheck failed: offset_end_ >file_offset_[file_ptr_end_]Check failed: file_ptr_end_ < files_.size() bad regex This could due to compiler version, g++-4.9 is neededfiles_.size() != 0UCannot find any files that matches the URI pattern curr=,begin=,end=,fileptr=,fileoffset=offset[file offset not calculated correctlyC/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/filesys.ccCheck failed: !IsSymlink(info.path.name)Symlink not supported in TemporaryDirectoryCouldn't remove file ; you may want to remove it manuallySuccessfully deleted temporary directory ~TemporaryDirectory(): Could not remove temporary directory /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/filesystem.hlstat(path.c_str(), &sb) == 0dmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes/Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/local_filesys.ccLocalFileSystem.GetPathInfo: detected symlink error: LocalFileSystem.GetPathInfo: LocalFileSystem.ListDirectory ...stdoutwbCheck failed: allow_null LocalFileSystem::Open "": Check failed: std::fwrite(ptr, 1, size, fp_) == sizeFileStream.Write incompleteCheck failed: !std::fseek(fp_, static_cast(pos), SEEK_SET)NULLworkerrabit_reduce_buffer256MBrabit_task_idrabit_num_trialrabit_reduce_ring_mincountrabit_tracker_urirabit_tracker_portDMLC_TASK_IDDMLC_ROLEDMLC_NUM_ATTEMPTDMLC_TRACKER_URIDMLC_TRACKER_PORTDMLC_WORKER_CONNECT_RETRY%[^=]=%smapred_tip_idmapreduce_task_idhadoop_mode is set but cannot find mapred_task_idrabit_hadoop_modemapred_task_id%dmapred_map_tasksmapreduce_job_mapshadoop_mode is set but cannot find mapred_map_tasksrabit_world_sizeRabit Module currently only work with dmlc worker, quit this program by exit 0 can only call Init oncestart%sprintconnect to (failed): [%s] Connectretry connect to ip(retry time %d): [%s] ReConnectLink failure 1ReConnectLink failure 2sync::Invalid tracker message, init failureReConnectLink failure 3ReConnectLink failure 4must keep rank to same if the node already have oneReConnectLink fail to bind the ports specifiedReConnectLink failure 5ReConnectLink failure 6ReConnectLink failure 7ReConnectLink failure 8ReConnectLink failure 9ReConnectLink failure 10ReConnectLink failure 12ReConnectLink failure 13ReConnectLink failure, link rank inconsistentOverride a link that is activeReConnectLink failure 14ReConnectLink failure 15ReConnectLink: bad socketcannot find parent in the linkcannot find prev ring in the linkcannot find next ring in the linkbuffer size inconsistentmust assign buffer_sizeAllreduce: size checkAllreduce: boundary errorBroadcast: root should be smaller than world sizeneed to assume rank structurewrite ptr boundary check[%d] read_ptr boundary checkfail to get host nameSocket::Close double close the socket or close without createerror during send SendStr%lu%cinvalid format for %sinvalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB}Createcannot obtain address of %sDoes not support IPv6Socket %s Error:%sSendAllRecvAllSetKeepAliveSO_LINGER0.0.0.0TryBindHostGetSockErrorerror during send RecvStrAcceptSetNonBlock-1SetNonBlock-2too large type_nbytes=%lu, buffer_size=%luPollReadToRingBuffer: buffer not allocatedReadToRingBuffer: max_size_read checkAllreduce: boundary checkAllreduce failedBroadcast failedInitAfterException: not implementedrabit_global_replicarabit_local_replicaShutdown: check point must return trueShutdown: check ack must return trueneed to set rabit_local_replica larger than 1 to checkpoint local_model[%d] local model inconsistent, nlocal=%dread in version numberlocal model inconsistent, nlocal=%dcheck ack must return trueCan only call Checkpoint/LoadCheckPoint always withor without local_model, but not mixed casecheck point must return true[%d] save global checkpoint #%d must already gone badwrong oob msgshould already read past markBUGwrong Ack MSGmust know the error sourcerecover[%d] Allreduce size inconsistent, distin=%lu, size=%lu, reporting=%lu Too many nodes went down and we cannot recover..cannot get and receive requestrequest result inconsistentTryRecoverDataTryDecideRoutingrecv_link must be activeboundary check[%d] recovered from local checkpoint version %d LoadCheckPoint: too many nodes fails, cannot recover local stateTryGetResult::Checkpointzero size check point is not allowedAllreduce Recovered data size do not match the specification of function call. Please check if calling sequence of recovered program is the same the original one in current VersionNumbermust only set seqno for normal operationscheck ack & check pt cannot occur together with normal opsmin seq buglocal chkpt space inconsistentinvalid local replicaTryCheckinLocalState must have exactly 1 stateRingPassing: boundary check1RingPassing: boundary check2RingPassing: boundary check3there is nothing to be droppedcannot allocate 0 size memoryPushTemp seqid inconsistentPushTemp inconsistentreporter:status:Rabit Phase[%03d] Operation %03d parent must be 0invalie stage idinvalid stageMsgPassing invalid stagerabit::Finalize engine is not initialized or already been finalized.the rabit has not been initializedcannot initialize reduce handle twicemust intialize handle to call AllReduceunknown enum_opunknown data_typeDataType does not support bitwise or operation%s Read pickle stringnot implemented LPXQ!QaQX Q! aQQ<!'-p =0''!P% (P+5x`68F IȽPRX\P_@ahjTz`} <,@x0@  0P\(@p`XlЫPxpp @(@pp<Lp``pH    `0| !$D%36A0CPDUV8pW\Z\]`^ szH}xЃTdp PP0(+P68:=> D0pEDGXpIh@LxNOP`QRS@X,[`_0abc e0gh(0m8pl0t@v xzz{00}L ~h@p0D`| pp8h|`0pP@P``$8 x P8Lt @$@/02D2T3p8@;`?C(PFXpLPN@R0Td@Y^`0fh80~`P ( P08T $P0`|P$|`4dp,pP@ (<L Pp$PH#XP$lP/023 =@IDK`LtPpSTWb, f`Php0i0llqt,0w\@|`8@T@@0X`|L |0$40Lpdpp|0P <!p$P()*0,,$`6x70809PD4`IpKPL@\T^pcPek$pt s8Hh`P  p( ` | p  P   P8 ` `L \      P( < L d @ ;,L$c`kln w zH@{\0~l 0(<Tl@`tH dtD@T`TPp@@0,l!'P-H<O@TXP[ ]^g0iTjplmnppssPy(pzDzT00ppHPX$TP0L \   p!P$!x!!!!p "D"@T" d" "@" #P#\$l$|$@$$@$ $8% h% %p%`%&pT&`d&t& &`2'I(N(pn*q+t8+tH+wp+ ,,8,H,p, - -d-t--0--.$.P4.`..P,/\////0$0D0T0`d0`0P0000`12D2h22p2@ 20 H3P x3 3 3 3 3p 44@ X4 |4P 4 4 4 $5p 45 D5" x5$ 5% 5`& 5 N d6a 6 g 6l 6n 6po 7p 7@r (7r 87@z 7{ 7| 7 ~ 7p 7@ h8 8 8P 09 D9 T9 9 : @: x:` :П : : P; ; ;P ; ; < <й <л < ,=p P= t=P = = =` 0> D> T> > ?0 @? x?@ ? @ $@ 4@0 @ @ A XA A AP A TB tB B B C02 dD05 D5 Dp6 D< E ? 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