vendor/libxgboost.dylib in xgb-0.2.1 vs vendor/libxgboost.dylib in xgb-0.3.0
- old
+ new
@@ -1,3340 +1,3017 @@
- x __TEXT 0 0 __text __TEXT ! ! __stubs __TEXT & & __stub_helper __TEXT __gcc_except_tab__TEXT __const __TEXT P *e P __cstring __TEXT z/ z/ __unwind_info __TEXT \ M \ 8 __DATA_CONST 0 0 __got __DATA_CONST 0
0 __mod_init_func __DATA_CONST = = __const __DATA_CONST > x > x __DATA 0 __la_symbol_ptr __DATA X __thread_vars __DATA X X __data __DATA 0 0 __thread_ptrs __DATA P H P w __thread_bss __DATA
- __bss __DATA 0 __common __DATA ( H __LINKEDIT
- h
-
0 @rpath/libxgboost.dylib " 0 0 0 8 ` p | Xk P
- n сcj5D+oA2
+ H x __TEXT __text __TEXT __stubs __TEXT ; > ; __stub_helper __TEXT B > B __gcc_except_tab__TEXT 4L 4L __const __TEXT { __cstring __TEXT c c __unwind_info __TEXT 43 l 43 8 __DATA_CONST __got __DATA_CONST 5 __mod_init_func __DATA_CONST __const __DATA_CONST 0 ` 0 x __DATA P! @ P! __la_symbol_ptr __DATA P! P! Y __thread_vars __DATA Y! Y! __data __DATA Z! ` Z! __thread_ptrs __DATA b! H b! __thread_bss __DATA (c!
+ __bss __DATA m! ` __common __DATA ! H __LINKEDIT !
p!
0 @rpath/libxgboost.dylib " 0 p! ` `w! H ! X% " ! " 2 $ L# ,g& ` P " 8 T& S#|G71fѦ2
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N5rabit6engine13AllreduceBaseE N5rabit6engine7IEngineE N5rabit6engine15AllreduceRobustE N5rabit5c_api11ReadWrapperE N5rabit5c_api12WriteWrapperE XGBoost 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.cc Check failed: mat.info.num_col_ <= num_col : num_col= vs mat.info.num_row_ <= num_row mat.info.num_row_ == offset_vec.size() - 1 Check failed: nan_missing There are NAN in the matrix, however, you did not set missing=NAN Check failed: !badnan[i] float32 float64 bool8 int32 int8 int16 int64 Unknown data table type. DMatrix/Booster has not been intialized or has already been disposed. src.info.group_ptr_.size() == 0U slice does not support group structure Check failed: iter->Next() static_cast<xgboost::bst_ulong>(ridx) < batch.Size() label weight base_margin Unknown float field name root_index Unknown uint field name r w text allocator<T>::allocate(size_t n) 'n' exceeds maximum supported size Check failed: at_first_ cannot reset NativeDataIter [ ] : %02d:%02d:%02d
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Check failed: static_cast<std::shared_ptr<DMatrix>*>(handle) ->get() ->Info() .group_ptr_.size() == 0U : slice does not support group structure Check failed: dynamic_cast<data::SimpleDMatrix*>(dmat) Slice only supported for SimpleDMatrix currently. XGDMatrixSetGroup is deprecated, use `XGDMatrixSetUIntInfo` instead. group label weight base_margin Unknown float field name group_ptr Unknown comp uint field name with comparison json str.size() > 2 str[0] == '{' r w text allocator<T>::allocate(size_t n) 'n' exceeds maximum supported size Check 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.h Check failed: _count >= 0 Check failed: _ptr || _count == 0 eval_metric SAVED_PARAM_ Check failed: learner_->GetAttr(attr_name, &saved_param_value) read can not have position excceed buffer length AssertError:%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.h fid == static_cast<int>(names_.size()) ( vs. i q int float unknown feature type, use i for indicator and q for quantity HistCutMatrix /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/common/hist_util.cc Row does not lie in any group!
- nthread == omp_get_num_threads() summary_array.size() == in_sketchs->size() cut.size() <= std::numeric_limits<uint32_t>::max() cut_size > row_ptr.back() Check failed: cbegin != cend cut.cut.size() > 0U ibegin + inst.size() == iend ======== Monitor: ======== /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/common/./timer.h Timer 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.h Check 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.h invalid init parameter Check failed: nlevel <= limit_size * eps Check failed: 0 <= index_ && index_ != span_->size() Check failed: index_ < span_->size() mingap= , maxgap= , wgap= Check failed: size <= sa.size + sb.size bug in combine fi.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 < n quantile: 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.cc Size() == other.Size() Size() == other.size() /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/data.cc Check failed: fi->Read(&version, sizeof(version)) == sizeof(version) MetaInfo: invalid version Check failed: version >= 1 && version <= kVersion MetaInfo: unsupported file version Check failed: fi->Read(&num_row_, sizeof(num_row_)) == sizeof(num_row_) MetaInfo: invalid format Check 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 type group cache_file.find('#') == std::string::npos Only one `#` is allowed in file path for cache file specification. .r - XGBOOST_TEST_NPART Load part of data of parts auto matrix with entries loaded from .group groups are loaded from .base_margin base_margin are loaded from .weight weights are loaded from .row.page Unknown format type raw Check failed: batch.index != nullptr offset_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.h Not implemented Invalid Parameter format for expect but value=' optional, default= , required Required parameter is not presented value 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.h enum_back_map_.count(value) != 0U Value not found in enum declared map::at: key not found Invalid Input: ' ', valid values are: /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/simple_csr_source.cc Check failed: info.qids_.empty() || info.qids_.size() == info.num_row_ Check failed: fi->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic) invalid input file format tmagic == kMagic invalid format, magic number mismatch /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/simple_dmatrix.cc Check failed: page_ != nullptr Check 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.cc Check failed: source_ != nullptr Raw binary data format. /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_raw_format.cc page->offset.Size() != 0U Invalid SparsePage file fi->Read(dmlc::BeginPtr(data_vec), (page->data).Size() * sizeof(Entry)) == (page->data).Size() * sizeof(Entry) fid + 1 < disk_offset_.size() disk_offset_[fid] > curr_offset fi->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] == 0 offset_vec.back() == page.data.Size() /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_source.cc cache_shards.size() != 0U finfo->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic) Check failed: fi->Read(&format) Invalid page format Writing to in MB/s, written SparsePageSource::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.h Check failed: !producer_sig_processed_ unique_lock::unlock: not locked Check failed: out_data_ != NULL Calling Value at beginning or end? thread constructor failed Check failed: producer_sig_ == kDestroy Check failed: cell != __null || produce_end_.load(std::memory_order_acquire) Check failed: producer_sig_ != kDestroy Check failed: producer_sig_ == kProduce Make 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.cc name_shards.size() == format_shards.size() Check failed: *out_page == nullptr Check failed: qrecycle_.Pop(out_page) SparsePage::Writer Finished writing to GBLinearModelParam GBLinearTrainParam Linear booster, implement generalized linear model. num_feature Number of features used in classification. num_output_group Number 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.h key has already been registered in updater shotgun Update algorithm for linear model. One of shotgun/coord_descent tolerance Stop if largest weight update is smaller than this number. max_row_perbatch Maximum rows per batch. string Out of range value for , value=' pos <= value.length() Some trailing characters could not be parsed: ' Out of range value No 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:
+ [bt] ( ) _Z DMLC_LOG_STACK_TRACE_DEPTH %zu /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/include/xgboost/data.h Check failed: impl_ != nullptr /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/include/xgboost/span.h Check failed: _idx < size() write position exceed fixed buffer size AssertError:%s, shutting down process
+ AssertError:%s, rabit is configured to keep process running
+ read can not have position excceed buffer length /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/include/xgboost/feature_map.h fid == static_cast<int>(names_.size()) ( vs. i q int float unknown feature type, use i for indicator and q for quantity Check failed: _ptr || _count == 0 HistogramCuts /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/common/hist_util.cc Building quantile cut on a sparse dataset. Building quantile cut on a dense dataset or distributed environment. Total number of hist bins: end_col >= beg_col Build nthreads > 0 page.Size() <= dmat->Info().num_col_ Load balance ;unknown;unknown;0;0;; SingleThreadBuild: Concat nthread == omp_get_num_threads() summary_array.size() == in_sketchs->size() N/A p_cuts_->cut_values_.size() <= std::numeric_limits<uint32_t>::max() cut_size > p_cuts_->cut_ptrs_.back() cut.Values().size() > 0U ibegin + inst.size() == iend sibling.size() == size parent.size() == size SparseCuts DenseCuts /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/common/./hist_util.h Row does not lie in any group! /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/common/./quantile.h invalid init parameter Check failed: nlevel <= limit_size * eps Check failed: index_ != span_->size() Check failed: index_ < span_->size() mingap= , maxgap= , wgap= Check failed: size <= sa.size + sb.size bug in combine check quantile stats, nbig= , n= srcsize= , maxsize= , range= , chunk= Check failed: nbig < n quantile: too many large chunk ] rmin= , rmax= , wmin= , v= fi.Read(&this->size, sizeof(this->size)) == sizeof(this->size) fi.Read(this->data, this->size * sizeof(Entry)) == this->size * sizeof(Entry) /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/common/host_device_vector.cc Size() == other.Size() Size() == other.size() /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/common/io.cc pointer_ <= buffer_.size() Check failed: out Opening failed: /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/common/io.h Not implemented " ": null \ \\ \" \b \f \n \r \t \u%04x false String Number Object Array Boolean Integer /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/common/json.cc Object of type can not be indexed by Integer. can not be indexed by string. Please try obtaining std::string first. Unknown construct , around character:
Unknown escape Expecting null value "null" ch != -1 cursor_.Pos(): , raw_str_.size(): exp > (kExpMax - digit) / 10 Overflow Check failed: is_float rue Expecting boolean value "true". alse Expecting boolean value "false". /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/include/xgboost/json.h beg <= size_ Expecting: " ", got: " " C Invalid cast, from to statistic count elapsed /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/common/timer.cc Timer for did not get stopped properly. s, calls @ us ======== Monitor: ======== From rank: version /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/common/version.cc 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 again. fi->Read(&read[0], verstr.size()) == verstr.size() fi->Read(&major, sizeof(major)) == sizeof(major) fi->Read(&minor, sizeof(major)) == sizeof(minor) fi->Read(&patch, sizeof(major)) == sizeof(patch) . num_row num_col num_nonzero labels weights /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/data.cc field_cnt == kNumField Wrong number of fields major == 1 Binary DMatrix generated by XGBoost: is no longer supported. Please process and save your data in current version: again. Check failed: fi->Read(&num_field) MetaInfo: invalid format num_field >= expected_num_field MetaInfo: insufficient number of fields (expected at least fields, but the binary file only contains fields.) MetaInfo: the given binary file contains extra fields which will be ignored. Unknown data type Unknown metainfo: XGBoost version is not compiled with GPU support cache_file.find('#') == std::string::npos Only one `#` is allowed in file path for cache file specification. .r - XGBOOST_TEST_NPART Load part of data of parts auto matrix with entries loaded from csv libsvm 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=csv Encountered parser error:
+ .group groups are loaded from .base_margin base_margin are loaded from .weight weights are loaded from self_offset.size() == other_offset.size() self_data.size(): other_data.size(): beg <= data.size() ptr < offset.size() MetaInfo: Invalid format. Check failed: strm->Read(&name) name == expected_name Expected field: , got: Check failed: strm->Read(&type) Check failed: type == expected_type Expected field of type: got field type: Check failed: strm->Read(&is_scalar) Check failed: is_scalar Expected field to be a scalar; got a vector Check failed: strm->Read(field, sizeof(T)) Check failed: !is_scalar to be a vector; got a scalar Check failed: strm->Read(&shape.first) Check failed: strm->Read(&shape.second) shape.second == 1 Number of columns is expected to be 1. Check failed: strm->Read(field) Invalid Parameter format for expect but value=' optional, default= , required Required parameter is not presented value for Parameter exceed bound [ should be greater equal to should be smaller equal to optional, default= ' /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./parameter.h enum_back_map_.count(value) != 0U Value not found in enum declared map::at: key not found Invalid Input: ' ', valid values are: .row.page /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.h cache_shards.size() != 0U Writing in MB/s, written Check failed: qids.empty() || qids.size() == info.num_row_ SparsePageSource::CreateRowPage Finished writing to raw /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_writer.h name_shards.size() == format_shards.size() thread constructor failed SparsePageWriter Finished writing to Unknown format type Check failed: *out_page == nullptr Check failed: qrecycle_.Pop(out_page) key >= builder_base_row_offset finfo->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic) tmagic == kMagic invalid format, magic number mismatch Check failed: fi->Read(&format) Invalid page format /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/threadediter.h Check failed: !producer_sig_processed_.load(std::memory_order_acquire) unique_lock::unlock: not locked Check failed: producer_sig_.load(std::memory_order_acquire) == kProduce Make sure you call BeforeFirst not inconcurrent with Next! Check failed: produce_end_.load(std::memory_order_acquire) Check failed: out_data_ != NULL Calling Value at beginning or end? Check failed: producer_sig_.load(std::memory_order_acquire) == kDestroy Check failed: cell != __null || produce_end_.load(std::memory_order_acquire) Check failed: producer_sig_.load(std::memory_order_acquire) != kDestroy No thread float32 float64 bool8 int32 int8 int16 int64 /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/adapter.h Unknown data table type. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page.cc Internal Error: XGBoost is not compiled with CUDA but EllpackPage is required /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page_source.cc Internal Error: XGBoost is not compiled with CUDA but EllpackPageSource is required /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/simple_csr_source.cc Check failed: fi->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic) invalid input file format /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.cc param.gpu_id >= 0 param.max_bin >= 2 /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.h Check failed: page_ != nullptr /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.cc Check failed: cast .col.page .sorted.col.page Check failed: source_ != nullptr /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.h Unknown page type: Writing to SparsePageSource: Finished writing to Raw binary data format. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_raw_format.cc page->offset.Size() != 0U Invalid SparsePage file fi->Read(dmlc::BeginPtr(data_vec), (page->data).Size() * sizeof(Entry)) == (page->data).Size() * sizeof(Entry) fid + 1 < disk_offset_.size() disk_offset_[fid] > curr_offset fi->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] == 0 offset_vec.back() == page.data.Size() GBLinearTrainParam gblinear Linear booster, implement generalized linear model. updater shotgun Update algorithm for linear model. One of shotgun/coord_descent tolerance Stop if largest weight update is smaller than this number. max_row_perbatch Maximum rows per batch. string /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.h key has already been registered in Out of range value for , value=' pos <= value.length() Some trailing characters could not be parsed: ' Out of range value No conversion could be performed /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h *p == ')' Invalid NAN literal /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear.cc get<String>(in["name"]) == "gblinear" model gpu_coord_descent __ 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.h fi->Read(¶m, sizeof(param)) == sizeof(param) DoBoost PredictBatchInternal /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./data.h PredictBatch /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/gblinear.cc ntree_limit == 0U GBLinear::Predict ntrees is only valid for gbtree predictor gblinear does not support prediction of leaf index GBLinear::PredictContribution: ntrees is only valid for gbtree predictor json { "bias": [ , ], "weight": [ ] } bias:
+ : /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/include/xgboost/gbm.h XGBoost version not compiled with GPU support. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.h fi->Read(¶m, sizeof(param)) == sizeof(param) DoBoost PredictBatchInternal PredictBatch ntree_limit == 0U GBLinear::Predict ntrees is only valid for gbtree predictor gblinear does not support prediction of leaf index GBLinear::PredictContribution: ntrees is only valid for gbtree predictor { "bias": [ , ], "weight": [ ] } bias:
weight:
- /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/gbm.cc Unknown gbm type GBTreeModelParam GBTreeTrainParam DartTrainParam gbtree Tree booster, gradient boosted trees. Tree booster, dart. Number of output groups to be predicted, used for multi-class classification. num_roots Tree updater sequence. Number of features used for training and prediction. size_leaf_vector Reserved option for vector tree. num_parallel_tree Number of parallel trees constructed during each iteration. This option is used to support boosted random forest. updater_seq grow_colmaker,prune process_type default update Whether to run the normal boosting process that creates new trees, or to update the trees in an existing model. predictor cpu_predictor Predictor algorithm type Enum ( exisit! )
- Enums: ), has not been registered in Alias sample_type uniform Different types of sampling algorithm. normalize_type forest Different types of normalization algorithm. rate_drop Fraction of trees to drop during the dropout. Whether at least one tree should always be dropped during the dropout. skip_drop Probability of skipping the dropout during a boosting iteration. learning_rate Learning rate(step size) of update. eta true false 1 0 boolean GBTree /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/gbm/gbtree_model.h GBTree: invalid model file fi->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.h fi->Read(¶m, sizeof(TreeParam)) == sizeof(TreeParam) param.num_nodes != 0 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<int>(deleted_nodes_.size()) == param.num_deleted param.num_trees == static_cast<int>(trees.size()) param.num_nodes == static_cast<int>(nodes_.size()) param.num_nodes == static_cast<int>(stats_.size()) distcol BoostNewTrees /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/gbtree.cc in_gpair->Size() % ngroup == 0U must have exactly ngroup*nrow gpairs CommitModel model_.trees.size() < model_.trees_to_update.size() out_preds->size() == n num_group == model_.param.num_output_group model_.param.size_leaf_vector == 0 size_leaf_vector is enforced to 0 so far preds.size() == p_fmat->Info().num_row_ * num_group drop trees, weight = LearnerModelParam LearnerTrainParam reg:squarederror /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/./common/timer.h bs64 /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/learner.cc header != "bs64" Base64 format is no longer supported in brick. binf fp.Read(&header[0], 4) == 4U fi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_) BoostLearner: wrong model format fi->Read(&len, sizeof(len)) == sizeof(len) fi->Read(&gap, sizeof(gap)) == sizeof(gap) fi->Read(&name_obj_[0], len) == len Check failed: fi->Read(&name_gbm_) gpu_predictor Parameter 'predictor' will be set to 'cpu_predictor' since XGBoost wasn't compiled with GPU support. count:poisson max_delta_step num_class /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/./common/io.h count_poisson_max_delta_step n_gpus gpu_id 0.7 Learner objective multi:softmax booster dart DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead. grow_histmaker,prune Tree method is selected to be 'hist', which uses a single updater grow_quantile_histmaker. grow_quantile_histmaker grow_gpu,prune grow_gpu_hist Unknown tree_method ( ) detected XGBoost version not compiled with GPU support. Check failed: matrix != nullptr num_col <= static_cast<uint64_t>(std::numeric_limits<unsigned>::max()) Unfortunately, XGBoost does not support data matrices with features or greater mparam_.num_feature != 0 0 feature is supplied. Are you using raw Booster interface? Check failed: obj_ == nullptr && gbm_ == nullptr UpdateOneIter Check failed: ModelInitialized() Always call InitModel or LoadModel before update PredictRaw GetGradient Check failed: weights.size() == info.group_ptr_.size() - 1 weights size: groups size: num rows: Number of weights should be equal to number of groups in ranking task. Check failed: tparam_.dsplit != DataSplitMode::kAuto Precondition violated; dsplit cannot be 'auto' in distributed mode Column-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 algoritms Tree 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 algorithms 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: gbm_ != nullptr Predict must happen after Load or InitModel BoostOneIter Always call InitModel or LoadModel before boost. EvalOneIter base_score Global 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_iteration Seed PRNG determnisticly via iterator number, this option will be switched on automatically on distributed mode. dsplit col row Data split mode for distributed training. tree_method approx gpu_exact Choice of tree construction method. test_flag Internal test flag nthread Number of threads to use. disable_default_eval_metric flag 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.cc Unknown linear updater LinearTrainParam Learning rate of each update. reg_lambda L2 regularization on weights. reg_alpha L1 regularization on weights. feature_selector cyclic shuffle thrifty greedy random Feature selection or ordering method. Number of devices to use. Primary device ordinal. lambda alpha CoordinateParam coord_descent Update linear model according to coordinate descent algorithm. top_k The 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.h CoordinateUpdater /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/linear/coordinate_common.h unknown coordinate selector: UpdateFeature Update 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.cc Unsupported feature selector for shotgun updater.
- Supported options are: {cyclic, shuffle} ConsoleLoggerParam WARNING: DEBUG: INFO: silent Do not print information during training. verbosity Flag to print out detailed breakdown of runtime. debug_verbose rmse Rooted mean square error. mae Mean absolute error. logloss Negative loglikelihood for logistic regression. poisson-nloglik Negative loglikelihood for poisson regression. gamma-deviance Residual deviance for gamma regression. gamma-nloglik Negative log-likelihood for gamma regression. error Binary classification error. tweedie-nloglik tweedie-nloglik@rho for tweedie regression. /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/metric/elementwise_metric.cu info.labels_.Size() != 0U label set cannot be empty preds.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.h gpu_id >= 0 gpu_id must be >= 0. n_gpus >= -1 n_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_devices Starting from gpu id: , there are only available devices, while n_gpus is set to: %f sscanf(param, "%f", &threshold_) == 1 unable to parse the threshold value for the error metric Check failed: param != nullptr tweedie-nloglik must be in format tweedie-nloglik@rho Check failed: rho_ < 2 && rho_ >= 1 tweedie 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.cc Unknown metric function MetricParam Number of GPUs to use for multi-gpu algorithms. gpu to use for objective function evaluation merror Multiclass classification error. mlogloss Multiclass negative loglikelihood. /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/metric/multiclass_metric.cu Check failed: preds.Size() % info.labels_.Size() == 0 label and prediction size not match nclass >= 1U mlogloss and merror are only used for multi-class classification, use logloss for binary classification Check failed: label_error >= 0 && label_error < static_cast<int32_t>(n_class) MultiClassEvaluation: label must be in [0, num_class), num_class= but found in label ams AMS metric for higgs. auc Area under curve for both classification and rank. aucpr Area under PR curve for both classification and rank. pre precision@k for rank. ndcg ndcg@k for rank. map map@k for rank. cox-nloglik Negative 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.cc AMS must be in format ams@k ams@ Check failed: !distributed metric AMS do not support distributed evaluation best-ams-ratio= label size predict size not match gptr.back() == info.labels_.Size() EvalAuc: group structure must match number of prediction Check failed: !auc_error AUC: the dataset only contains pos or neg samples EvalAucPR: group structure must match number of prediction AUC-PR: error in calculation AUC-PR: the dataset only contains pos or neg samples dat[0] <= dat[1] AUC-PR: AUC > 1.0 sum_auc <= static_cast<double>(ngroup) %u[-]? gptr.size() != 0U must specify group when constructing rank file gptr.back() == preds.Size() EvalRanklist: group structure must match number of prediction Cox metric does not support distributed evaluation HingeObjParam binary:hinge Hinge 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.cu labels are not correctly provided preds.size= , label.size= /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/objective/../common/transform.h Not part of device code. WITH_CUDA: SoftmaxMultiClassParam Softmax for multi-class classification, output class index. multi:softprob Softmax 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.cu Check failed: preds.Size() == (static_cast<size_t>(param_.num_class) * info.labels_.Size()) SoftmaxMultiClassObj: label size and pred size does not match SoftmaxMultiClassObj: 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.cc Objective candidate: Unknown objective function LambdaRankParam rank:pairwise Pairwise rank objective. rank:ndcg LambdaRank with NDCG as objective. LambdaRank with MAP as objective. num_pairsample Number of pair generated for each instance. fix_list_weight Normalize 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.cc Check failed: gptr.size() != 0 && gptr.back() == info.labels_.Size() group structure not consistent with #rows RegLossParam Regression with squared error. reg:logistic Logistic regression for probability regression task. binary:logistic Logistic regression for binary classification task. binary:logitraw Logistic regression for classification, output score before logistic transformation. reg:linear gpu:reg:linear Deprecated. Linear regression (computed on GPU). gpu:reg:logistic Deprecated. Logistic regression for probability regression task (computed on GPU). gpu:binary:logistic Deprecated. Logistic regression for binary classification task (computed on GPU). gpu:binary:logitraw Deprecated. Logistic regression for classification, output score before logistic transformation (computed on GPU) PoissonRegressionParam Possion regression for count data. survival:cox Cox regression for censored survival data (negative labels are considered censored). GammaRegressionParam reg:gamma Gamma regression for severity data. TweedieRegressionParam reg:tweedie Tweedie regression for insurance data. scale_pos_weight Scale 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.cu label 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.h Check failed: base_score > 0.0f && base_score < 1.0f base_score must be in (0,1) for logistic loss reg: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 nonnegative Check failed: last_abs_y <= abs_y CoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed! GammaRegression: label must be nonnegative tweedie_variance_power Tweedie variance power. Must be between in range [1, 2). TweedieRegression: label must be nonnegative Make predictions using CPU. /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/predictor/cpu_predictor.cc out_preds->Size() == n Warning: 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.cc Unknown predictor type /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/split_evaluator.cc Unknown SplitEvaluator ElasticNetParams elastic_net Use an elastic net regulariser MonotonicConstraintParams monotonic Enforces that the tree is monotonically increasing/decreasing w.r.t. specified features InteractionConstraintParams interaction Enforces interaction constraints on tree features L2 regularization on leaf weight L1 regularization on leaf weight Maximum delta step we allow each tree's weight estimate to be. If the value is set to 0, it means there is no constraint ElasticNet does not accept an inner SplitEvaluator monotone_constraints Constraint of variable monotonicity MonotonicConstraint must be given an inner evaluator Check failed: !std::isnan(mid) Check failed: nodeid < upper_.size() interaction_constraints Constraints 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 information Number of total features used InteractionConstraint 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.h ch == '[' Error at , Expect '{' but get ' Line , around ^` ` ch == ',' , JSON array expect ']' or ','. Get ' ' instead Check failed: !is_->fail() , Expect number TreeParam TrainParam { "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.cc unknown fmap type , "split": :[f , "gain": ,gain= , "children": [ ]} this->node_mean_values_.size() > 0U unique_path[i].pweight == 0 Unique path must have zero weight idx < names_.size() FeatureMap feature index exceed bound Number of start root of trees. Number of features used in tree construction. Size of leaf vector, reserved for vector tree min_split_loss Minimum loss reduction required to make a further partition. max_depth Maximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policy max_leaves Maximum number of leaves; 0 indicates no limit. max_bin if using histogram-based algorithm, maximum number of bins per feature grow_policy depthwise lossguide Tree 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_weight Minimum sum of instance weight(hessian) needed in a child. default_direction learn right Default direction choice when encountering a missing value subsample Row subsample ratio of training instance. colsample_bynode Subsample ratio of columns, resample on each node (split). colsample_bylevel Subsample ratio of columns, resample on each level. colsample_bytree Subsample ratio of columns, resample on each tree construction. opt_dense_col EXP Param: speed optimization for dense column. sketch_eps EXP Param: Sketch accuracy of approximate algorithm. sketch_ratio EXP Param: Sketch accuracy related parameter of approximate algorithm. Size of leaf vectors, reserved for vector trees parallel_option Different types of parallelization algorithm. cache_opt EXP Param: Cache aware optimization. refresh_leaf Whether the refresh updater needs to update leaf values. gpu to use for single gpu algorithms Number of GPUs to use for multi-gpu algorithms: -1=use all GPUs split_evaluator elastic_net,monotonic,interaction The criteria to use for ranking splits sparse_threshold percentage threshold for treating a feature as sparse enable_feature_grouping if >0, enable feature grouping to ameliorate work imbalance among worker threads max_conflict_rate when 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_group when grouping features, how much effort to expend to prevent singleton groups. We'll try to insert each feature into existing groups before creating a new group for that feature; to save time, only up to (max_search_group) of existing groups will be considered. If set to zero, ALL existing groups will be examined. gamma double /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/tree_updater.cc Unknown tree updater grow_colmaker Grow 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.cc tree.param.num_nodes == tree.param.num_roots ColMaker: can only grow new tree fmat.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.h features.size() > 0 /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./tree_model.h Check failed: node.IsLeaf() param.num_nodes < std::numeric_limits<int>::max() number of nodes in the tree exceed 2^31 ridx < position_.size() ridx exceed bound ridx= pos= prune trees.size() == 1U DistColMaker: only support one tree at a time Check failed: !tree[nid].IsLeaf() inconsistent reduce information nid >= 0 grow_local_histmaker Tree constructor that uses approximate histogram construction. grow_global_histmaker Tree constructor that uses approximate global proposal of histogram construction. grow_histmaker Tree 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.cc Check failed: param_.max_depth > 0 max_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.h TreeMaker: can only grow new tree root_index[i] < (unsigned)tree.param.num_roots root index exceed setting node2workindex_[nid] == static_cast<int>(wid) summary_array_.size() == sketchs_.size() offset == -2 this->wspace_.rptr.size() == (fset.size() + 1) * this->qexpand_.size() + 1 fid * 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.h ret > 0U Check failed: tree[nid].IsLeaf() sketch->temp.size < max_size invalid maximum size max_size= , stemp.size INFO: rmax= , sum_total= , naxt_goal= , size= sketch->temp.size <= max_size Finalize: invalid maximum size, max_size= , stemp.size= fid * 2 < fminmax_.size() fv= , hist.size= hist[ ]= , hist.last= istart != hist.size this->qexpand_.size() == 1U this->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.cc tree 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.cc Generating gmat: sec SyncHistograms BuildLocalHistograms BuildNodeStats Update out_preds.size() > 0U Check failed: (*p_last_tree_)[nid].IsLeaf() ColMakerHist: can only grow new tree Check failed: (param_.max_depth > 0 || param_.max_leaves > 0) max_depth or max_leaves cannot be both 0 (unlimited); at least one should be a positive quantity. max_depth cannot be 0 (unlimited) when grow_policy is depthwise. info.root_index_.size() == 0U min_nbins_per_feature > 0U EvaluateSplit ApplySplit upper_bound < static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) InitNewNode Check failed: d_step == +1 || d_step == -1 cut_ptr[fid] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) cut_ptr[fid + 1] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::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.h gmat.cut.row_ptr[fid + 1] - gmat.cut.row_ptr[fid] <= max_val Quantile::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.h row_ptr_[nid] != kMax row_ptr_[nid] == kMax SubtractionTrick BuildHist /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/common/row_set.h Check failed: e.begin != nullptr access element that is not in the set elem_of_each_node_.size() == 0U grow_fast_histmaker is deprecated, use grow_quantile_histmaker instead. refresh Refresher 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.cc batch.Size() < std::numeric_limits<unsigned>::max() grow_skmaker Approximate sketching maker. /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_skmaker.cc qexpand_.size() != 0U Syncher that synchronize the tree in all distributed nodes. LibSVMParserParam LibFMParserParam CSVParserParam libsvm libfm csv format File format indexing_mode If >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_column Column index (0-based) that will put into label. delimiter Delimiter used in the csv file. weight_column Column 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.h Check 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.h Check failed: fi->Read(&label) Bad RowBlock format Check 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/sec finish reading at %g MB/sec batch.field[i] <= std::numeric_limits<IndexType>::max() field exceed numeric bound of current type batch.index[i] <= std::numeric_limits<IndexType>::max() index exceed numeric bound of current type label.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.h finish reading at /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data.cc Unknown data type /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/./libsvm_parser.h param_.format == "libsvm" /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/./text_parser.h chunk.size != 0U qid: Check failed: out->label.size() + 1 == out->offset.size() Check failed: base <= 10 && base >= 2 sign == true /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/parser.h cannot call ParseNext /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/libfm_parser.h param_.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.h param_.format == "csv" Check failed: param_.label_column != param_.weight_column || param_.label_column < 0 Must have distinct columns for labels and instance weights Delimiter ' ' is not found in the line. Expected ' ' as the delimiter to separate fields. Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size() file:// hdfs:// viewfs:// /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io.cc Please compile with DMLC_USE_HDFS=1 to use hdfs s3:// http:// https:// Please compile with DMLC_USE_S3=1 to use S3 azure:// Please compile with DMLC_USE_AZURE=1 to use Azure unknown filesystem protocol stdin Check failed: part < nsplit invalid input parameter for InputSplit::Create indexed_recordio need to pass index file to use IndexedRecordIO recordio unknown 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.h name_cache.size() == 1U only one `#` is allowed in file path for cachefile specification Check failed: std::getline(is, kv.first, '=') Invalid uri argument format for key in arg Check failed: std::getline(is, kv.second) for value in arg name_args.size() == 1U rb /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/single_file_split.h Check failed: fp_ != NULL SingleFileSplit: fail to open Check failed: part_index == 0 && num_parts == 1 InputSplit 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.h Check failed: nread == sizeof(size) has invalid cache file format Check failed: fi_->Read(p->begin, size) == size BeforeFirst is not supported Check failed: this->InitCachedIter() Failed to initialize CachedIter ResetPartition 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.cc Check failed: begin != end /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/recordio_split.cc Check failed: fi->Read(&lrec, sizeof(lrec)) != 0 invalid record io format (reinterpret_cast<size_t>(begin) & 3UL) == 0U (reinterpret_cast<size_t>(end) & 3UL) == 0U Check failed: p >= pbegin + 2 Check failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->end Invalid RecordIO Format (reinterpret_cast<size_t>(chunk->begin) & 3UL) == 0U (reinterpret_cast<size_t>(chunk->end) & 3UL) == 0U Check failed: chunk->begin <= chunk->end Check failed: cflag == 1U Check 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.cc expanded_list.size() == 1ul IndexedRecordIOSplitter 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.cc Check failed: files_[i].size % align_bytes == 0 file do not align by bytes Check 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 needed files_.size() != 0U Cannot find any files that matches the URI pattern curr= ,begin= ,end= ,fileptr= ,fileoffset= offset[ file offset not calculated correctly C /Users/runner/runners/2.164.0/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/filesys.cc Check failed: !IsSymlink(info.path.name) Symlink not supported in TemporaryDirectory Couldn't remove file ; you may want to remove it manually Successfully 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.h lstat(path.c_str(), &sb) == 0 dmlc::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.cc LocalFileSystem.GetPathInfo: detected symlink error: LocalFileSystem.GetPathInfo: LocalFileSystem.ListDirectory . .. stdout wb Check failed: allow_null LocalFileSystem::Open " ": Check failed: std::fwrite(ptr, 1, size, fp_) == size FileStream.Write incomplete Check failed: !std::fseek(fp_, static_cast<long>(pos), SEEK_SET) NULL worker rabit_reduce_buffer 256MB rabit_task_id rabit_num_trial rabit_reduce_ring_mincount rabit_tracker_uri rabit_tracker_port DMLC_TASK_ID DMLC_ROLE DMLC_NUM_ATTEMPT DMLC_TRACKER_URI DMLC_TRACKER_PORT DMLC_WORKER_CONNECT_RETRY %[^=]=%s mapred_tip_id mapreduce_task_id hadoop_mode is set but cannot find mapred_task_id rabit_hadoop_mode mapred_task_id %d mapred_map_tasks mapreduce_job_maps hadoop_mode is set but cannot find mapred_map_tasks rabit_world_size Rabit Module currently only work with dmlc worker, quit this program by exit 0
- can only call Init once start %s print connect to (failed): [%s]
- Connect retry connect to ip(retry time %d): [%s]
- ReConnectLink failure 1 ReConnectLink failure 2 sync::Invalid tracker message, init failure ReConnectLink failure 3 ReConnectLink failure 4 must keep rank to same if the node already have one ReConnectLink fail to bind the ports specified ReConnectLink failure 5 ReConnectLink failure 6 ReConnectLink failure 7 ReConnectLink failure 8 ReConnectLink failure 9 ReConnectLink failure 10 ReConnectLink failure 12 ReConnectLink failure 13 ReConnectLink failure, link rank inconsistent Override a link that is active ReConnectLink failure 14 ReConnectLink failure 15 ReConnectLink: bad socket cannot find parent in the link cannot find prev ring in the link cannot find next ring in the link buffer size inconsistent must assign buffer_size Allreduce: size check Allreduce: boundary error Broadcast: root should be smaller than world size need to assume rank structure write ptr boundary check [%d] read_ptr boundary check fail to get host name Socket::Close double close the socket or close without create error during send SendStr %lu%c invalid format for %s invalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB} Create cannot obtain address of %s Does not support IPv6 Socket %s Error:%s SendAll RecvAll SetKeepAlive SO_LINGER 0.0.0.0 TryBindHost GetSockError error during send RecvStr Accept SetNonBlock-1 SetNonBlock-2 too large type_nbytes=%lu, buffer_size=%lu Poll ReadToRingBuffer: buffer not allocated ReadToRingBuffer: max_size_read check Allreduce: boundary check Allreduce failed Broadcast failed InitAfterException: not implemented rabit_global_replica rabit_local_replica Shutdown: check point must return true Shutdown: check ack must return true need to set rabit_local_replica larger than 1 to checkpoint local_model [%d] local model inconsistent, nlocal=%d read in version number local model inconsistent, nlocal=%d check ack must return true Can only call Checkpoint/LoadCheckPoint always withor without local_model, but not mixed case check point must return true [%d] save global checkpoint #%d
- must already gone bad wrong oob msg should already read past mark BUG wrong Ack MSG must know the error source recover [%d] Allreduce size inconsistent, distin=%lu, size=%lu, reporting=%lu
- Too many nodes went down and we cannot recover.. cannot get and receive request request result inconsistent TryRecoverData TryDecideRouting recv_link must be active boundary check [%d] recovered from local checkpoint version %d
- LoadCheckPoint: too many nodes fails, cannot recover local state TryGetResult::Checkpoint zero size check point is not allowed Allreduce 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 VersionNumber must only set seqno for normal operations check ack & check pt cannot occur together with normal ops min seq bug local chkpt space inconsistent invalid local replica TryCheckinLocalState must have exactly 1 state RingPassing: boundary check1 RingPassing: boundary check2 RingPassing: boundary check3 there is nothing to be dropped cannot allocate 0 size memory PushTemp seqid inconsistent PushTemp inconsistent reporter:status:Rabit Phase[%03d] Operation %03d
- parent must be 0 invalie stage id invalid stage MsgPassing invalid stage rabit::Finalize engine is not initialized or already been finalized. the rabit has not been initialized cannot initialize reduce handle twice must intialize handle to call AllReduce unknown enum_op unknown data_type DataType does not support bitwise or operation %s
- Read pickle string not implemented L P XQ ! QaQX Q! a Q Q< ! ' - p
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+ gblinear_train_param Check failed: this->updater_ DeprecatedGBLinearModelParam /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/gbm/gbm.cc Unknown gbm type cpu_predictor GBTree /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.cc DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using`tree_method` parameter instead. Check failed: this->configured_ Check failed: tparam_.GetInitialised() Using updaters: Tree method is automatically selected to be 'approx' for distributed training. Tree method is automatically set to 'approx' since external-memory data matrix is used. Tree method is automatically selected to be 'approx' for faster speed. To use old behavior (exact greedy algorithm on single machine), set tree_method to 'exact'. Using tree method: grow_histmaker,prune grow_colmaker,prune Tree method is selected to be 'hist', which uses a single updater grow_quantile_histmaker. grow_quantile_histmaker grow_gpu_hist Unknown tree_method ( ) detected BoostNewTrees ngroup != 0 in_gpair->Size() % ngroup == 0U must have exactly ngroup*nrow gpairs ups.size() == updaters_.size() Internal Error: mismatched updater sequence.
+ Specified updaters: Actual updaters: model_.trees.size() < model_.trees_to_update.size() CommitModel Check failed: configured_ gbtree get<String>(in["name"]) == "gbtree" gbtree_train_param predictor tree_method Loading from a raw memory buffer on CPU only machine. Change tree_method to hist. specified_updater GBTreeModelParam GBTreeTrainParam DartTrainParam Tree booster, gradient boosted trees. dart Tree booster, dart. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.h Check failed: cpu_predictor_ Data is on CUDA device, but XGBoost is not compiled with CUDA support. distcol num_trees Number of features used for training and prediction. size_leaf_vector Reserved option for vector tree. num_parallel_tree Number of parallel trees constructed during each iteration. This option is used to support boosted random forest. updater_seq Tree updater sequence. process_type default update Whether to run the normal boosting process that creates new trees, or to update the trees in an existing model. gpu_predictor Predictor algorithm type approx exact Choice of tree construction method. Enum ( exisit! )
+ Enums: ), has not been registered in Alias sample_type uniform Different types of sampling algorithm. normalize_type forest Different types of normalization algorithm. rate_drop Fraction of trees to drop during the dropout. Whether at least one tree should always be dropped during the dropout. skip_drop Probability of skipping the dropout during a boosting iteration. learning_rate Learning rate(step size) of update. eta true 1 0 boolean get<String>(in["name"]) == "dart" weight_drop out_preds.size() == n num_group == model_.learner_model_param_->num_output_group model_.param.size_leaf_vector == 0 size_leaf_vector is enforced to 0 so far preds.size() == p_fmat->Info().num_row_ * num_group dart_train_param drop trees, weight = /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.cc param.num_trees == static_cast<int32_t>(trees.size()) GBTree: invalid model file fi->Read(dmlc::BeginPtr(tree_info), sizeof(int32_t) * param.num_trees) == sizeof(int32_t) * param.num_trees param.num_trees == static_cast<int>(trees.size()) gbtree_model_param trees tree_info LearnerModelParamLegacy LearnerTrainParam GenericParameter gpu_id eval_metric CONFIG-offset: num_round Learner /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/learner.cc Check failed: IsA<Object>(in) learner learner_model_param objective gradient_booster booster attributes base_score num_feature num_class Check failed: !this->need_configuration_ Call Configure before saving model. Configure /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/include/xgboost/generic_parameters.h
+n_gpus: n_gpus Check failed: matrix != nullptr num_col <= static_cast<uint64_t>(std::numeric_limits<unsigned>::max()) Unfortunately, XGBoost does not support data matrices with features or greater mparam_.num_feature != 0 0 feature is supplied. Are you using raw Booster interface? multi:softprob num_output_group multi:softmax max_delta_step count:poisson 0.7 _param verbosity
+Parameters: { } might not be used.
-
+ This may not be accurate due to some parameters are only used in language bindings but
+ passed down to XGBoost core. Or some parameters are not used but slip through this
+ verification. Please open an issue if you find above cases.
- h hw
+ UpdateOneIter PredictRaw GetGradient Check failed: tparam_.dsplit != DataSplitMode::kAuto Precondition violated; dsplit cannot be 'auto' in distributed mode Column-wise data split is currently not supported. Check failed: weights.Size() == info.group_ptr_.size() - 1 weights size: groups size: num rows: Number of weights should be equal to number of groups in ranking task. Number of columns does not match number of features in booster. learner_model_param_.num_feature == p_fmat->Info().num_col_ Columns: Features: Check failed: gbm_ != nullptr Predict must happen after Load or configuration BoostOneIter EvalOneIter multiple_predictions <= 1 Perform one kind of prediction at a time. bs64 header != "bs64" Base64 format is no longer supported in brick. binf fp.Read(&header[0], 4) == 4U fi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_) BoostLearner: wrong model format Check failed: fi->Read(&tparam_.objective) Check failed: fi->Read(&tparam_.booster) SAVED_PARAM_ count_poisson_max_delta_step metrics Loading model from XGBoost < 1.0.0, consider saving it again for improved compatibility rabit_bootstrap_cache ; The model hasn't been built yet. Are you using raw Booster interface? learner_train_param generic_param Model Config fp.Read(&header[0], header.size()) == serialisation_header_.size() Check failed: header == serialisation_header_
-
+ If you are loading a serialized model (like pickle in Python) generated by older
+ XGBoost, please export the model by calling `Booster.save_model` from that version
+ first, then load it back in current version. There's a simple script for helping
+ the process. See:
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+ https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html
+
+ for reference to the script, and more details about differences between saving model and
+ serializing.
+
+ fp.Read(&sz, sizeof(sz)) == sizeof(sz) sz > 0 Global 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. int (non-negative) dsplit col row Data split mode for distributed training. disable_default_eval_metric Flag to disable default metric. Set to >0 to disable Gradient booster used for training. reg:squarederror Objective function used for obtaining gradient. Random number seed during training. random_state seed_per_iteration Seed PRNG determnisticly via iterator number, this option will be switched on automatically on distributed mode. nthread Number of threads to use. n_jobs The primary GPU device ordinal. gpu_page_size GPU page size when running in external memory mode. enable_experimental_json_serialization Enable using JSON for memory serialization (Python Pickle, rabit checkpoints etc.). validate_parameters Enable checking whether parameters are used or not. validate_features Enable validating input DMatrix.
+ Deprecated. Single process multi-GPU training is no longer supported.
+ Please switch to distributed training with one process per GPU.
+ This can be done using Dask or Spark. See documentation for details. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/linear/linear_updater.cc Unknown linear updater LinearTrainParam Learning rate of each update. reg_lambda L2 regularization on weights. reg_alpha L1 regularization on weights. feature_selector cyclic shuffle thrifty greedy random Feature selection or ordering method. lambda alpha CoordinateParam coord_descent Update linear model according to coordinate descent algorithm. top_k The number of top features to select in 'thrifty' feature_selector. The value of zero means using all the features. linear_train_param coordinate_param CoordinateUpdater /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.h unknown coordinate selector: UpdateFeature Update linear model according to shotgun coordinate descent algorithm. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/linear/updater_shotgun.cc Unsupported feature selector for shotgun updater.
+ Supported options are: {cyclic, shuffle} ConsoleLoggerParam WARNING: DEBUG: INFO: silent Do not print information during training. Flag to print out detailed breakdown of runtime. debug_verbose rmse Rooted mean square error. rmsle Rooted mean square log error. mae Mean absolute error. logloss Negative loglikelihood for logistic regression. poisson-nloglik Negative loglikelihood for poisson regression. gamma-deviance Residual deviance for gamma regression. gamma-nloglik Negative log-likelihood for gamma regression. error Binary classification error. tweedie-nloglik tweedie-nloglik@rho for tweedie regression. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/metric/elementwise_metric.cu label set is empty preds.Size() == info.labels_.Size() label and prediction size not match, hint: use merror or mlogloss for multi-class classification %f sscanf(param, "%f", &threshold_) == 1 unable to parse the threshold value for the error metric Check failed: param != nullptr tweedie-nloglik must be in format tweedie-nloglik@rho Check failed: rho_ < 2 && rho_ >= 1 tweedie variance power must be in interval [1, 2) tweedie-nloglik@ /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/metric/metric.cc Unknown metric function merror Multiclass classification error. mlogloss Multiclass negative loglikelihood. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/metric/multiclass_metric.cu info.labels_.Size() != 0U label set cannot be empty Check failed: preds.Size() % info.labels_.Size() == 0 label and prediction size not match nclass >= 1U mlogloss and merror are only used for multi-class classification, use logloss for binary classification Check failed: label_error >= 0 && label_error < static_cast<int32_t>(n_class) MultiClassEvaluation: label must be in [0, num_class), num_class= but found in label ams AMS metric for higgs. auc Area under curve for both classification and rank. aucpr Area under PR curve for both classification and rank. pre precision@k for rank. ndcg ndcg@k for rank. map map@k for rank. cox-nloglik Negative log partial likelihood of Cox proportioanl hazards model. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/metric/rank_metric.cc AMS must be in format ams@k ams@ Check failed: !distributed metric AMS do not support distributed evaluation best-ams-ratio= label size predict size not match gptr.back() == info.labels_.Size() EvalAuc: group structure must match number of prediction dat[1] > 0.0f AUC: the dataset only contains pos or neg samples EvalAucPR: group structure must match number of prediction Check failed: !auc_error AUC-PR: error in calculation AUC-PR: the dataset only contains pos or neg samples dat[0] <= dat[1] AUC-PR: AUC > 1.0 %u[-]? gptr.size() != 0U must specify group when constructing rank file gptr.back() == preds.Size() EvalRanklist: group structure must match number of prediction Cox metric does not support distributed evaluation binary:hinge Hinge loss. Expects labels to be in [0,1f] /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/objective/hinge.cu labels are not correctly provided preds.size= , label.size= info.weights_.Size() == ndata Number of weights should be equal to number of data points. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/objective/../common/transform.h Not part of device code. WITH_CUDA: SoftmaxMultiClassParam Softmax for multi-class classification, output class index. Softmax for multi-class classification, output probability distribution. Number of output class in the multi-class classification. softmax_multiclass_param /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/objective/multiclass_obj.cu Check failed: preds.Size() == (static_cast<size_t>(param_.num_class) * info.labels_.Size()) SoftmaxMultiClassObj: label size and pred size does not match.
+ label.Size() * num_class: num_class: preds.Size(): SoftmaxMultiClassObj: label must be in [0, num_class). Check failed: _offset < size() || size() == 0 Check failed: (_count == dynamic_extent) || (_offset + _count <= size()) Check failed: (index_ + n) <= span_->size() Check failed: span_ == rhs.span_ Objective candidate: /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/objective/objective.cc Unknown objective function: ` `
+ LambdaRankParam Pairwise rank objective. LambdaRank with NDCG as objective. LambdaRank with MAP as objective. rank:pairwise rank:ndcg rank:map num_pairsample Number of pair generated for each instance. fix_list_weight Normalize the weight of each list by this value, if equals 0, no effect will happen lambda_rank_param /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/objective/rank_obj.cu Check failed: gptr.size() != 0 && gptr.back() == info.labels_.Size() group structure not consistent with #rows group ponter size: labels size: group pointer back: Computing gradients on CPU. RegLossParam Regression with squared error. Regression with root mean squared logarithmic error. Logistic regression for probability regression task. Logistic regression for binary classification task. Logistic regression for classification, output score before logistic transformation. reg:linear PoissonRegressionParam Possion regression for count data. survival:cox Cox regression for censored survival data (negative labels are considered censored). reg:gamma Gamma regression for severity data. TweedieRegressionParam reg:tweedie Tweedie regression for insurance data. reg:squaredlogerror reg:logistic binary:logistic binary:logitraw scale_pos_weight Scale the weight of positive examples by this factor reg_loss_param /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/objective/regression_obj.cu Label set is empty. label must be greater than -1 for rmsle so that log(label + 1) can be valid. label must be in [0,1] for logistic regression /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/objective/./regression_loss.h Check failed: base_score > 0.0f && base_score < 1.0f base_score must be in (0,1) for logistic loss, got: reg:linear is now deprecated in favor of reg:squarederror. Maximum delta step we allow each weight estimation to be. This parameter is required for possion regression. poisson_regression_param PoissonRegression: label must be nonnegative Check failed: last_abs_y <= abs_y CoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed! GammaRegression: label must be nonnegative tweedie_variance_power Tweedie variance power. Must be between in range [1, 2). tweedie_regression_param TweedieRegression: label must be nonnegative Make predictions using CPU. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.cc Check failed: cache_ model.learner_model_param_->num_output_group != 0 out_preds->Size() == n 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 ncolumns != 0 /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/predictor/predictor.cc Unknown predictor type /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/constraints.cc Failed to parse feature interaction constraint:
+ With error:
+ newsize != 0 /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./json.h ch == '[' Error at , Expect '[' but get ' Line , around ^` ` ch == ',' , JSON array expect ']' or ','. Get ' ' instead Check failed: !is_->fail() , Expect number /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/split_evaluator.cc Unknown SplitEvaluator elastic_net Use an elastic net regulariser monotonic Enforces that the tree is monotonically increasing/decreasing w.r.t. specified features ElasticNet does not accept an inner SplitEvaluator Check failed: r->params_ MonotonicConstraint must be given an inner evaluator Check failed: c->params_ Check failed: !std::isnan(mid) Check failed: nodeid < upper_.size() TreeParam TrainParam /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/tree_model.cc Unknown Model Builder: Dump text representation of tree Dump json representation of tree GraphvizParam dot Dump graphviz representation of tree fi->Read(¶m, sizeof(TreeParam)) == sizeof(TreeParam) param.num_nodes != 0 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<int>(deleted_nodes_.size()) == param.num_deleted param.num_nodes == static_cast<int>(nodes_.size()) param.num_nodes == static_cast<int>(stats_.size()) param.deprecated_num_roots == 1 tree_param n_nodes != 0 loss_changes loss_changes.size() == n_nodes sum_hessian sum_hessian.size() == n_nodes base_weights base_weights.size() == n_nodes leaf_child_counts leaf_child_counts.size() == n_nodes left_children lefts.size() == n_nodes right_children rights.size() == n_nodes parents parents.size() == n_nodes split_indices indices.size() == n_nodes split_conditions conds.size() == n_nodes default_left default_left.size() == n_nodes static_cast<bst_node_t>(deleted_nodes_.size()) == param.num_deleted num_nodes get<String>(out["tree_param"]["num_nodes"]) == std::to_string(param.num_nodes) this->node_mean_values_.size() > 0U unique_path[i].pweight == 0 Unique path must have zero weight Number of features used in tree construction. Size of leaf vector, reserved for vector tree min_split_loss Minimum loss reduction required to make a further partition. max_depth Maximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policy max_leaves Maximum number of leaves; 0 indicates no limit. max_bin if using histogram-based algorithm, maximum number of bins per feature grow_policy depthwise lossguide Tree 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_weight Minimum sum of instance weight(hessian) needed in a child. L2 regularization on leaf weight L1 regularization on leaf weight default_direction learn right Default direction choice when encountering a missing value Maximum delta step we allow each tree's weight estimate to be. If the value is set to 0, it means there is no constraint subsample Row subsample ratio of training instance. colsample_bynode Subsample ratio of columns, resample on each node (split). colsample_bylevel Subsample ratio of columns, resample on each level. colsample_bytree Subsample ratio of columns, resample on each tree construction. sketch_eps EXP Param: Sketch accuracy of approximate algorithm. sketch_ratio EXP Param: Sketch accuracy related parameter of approximate algorithm. cache_opt EXP Param: Cache aware optimization. refresh_leaf Whether the refresh updater needs to update leaf values. monotone_constraints Constraint of variable monotonicity interaction_constraints Constraints 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 information split_evaluator elastic_net,monotonic The criteria to use for ranking splits sparse_threshold percentage threshold for treating a feature as sparse enable_feature_grouping if >0, enable feature grouping to ameliorate work imbalance among worker threads max_conflict_rate when 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_group when grouping features, how much effort to expend to prevent singleton groups. We'll try to insert each feature into existing groups before creating a new group for that feature; to save time, only up to (max_search_group) of existing groups will be considered. If set to zero, ALL existing groups will be examined. gamma double {nid}:[{fname}] yes={yes},no={no} {nid} {fname} {yes} pos != std::string::npos idx < names_.size() FeatureMap feature index exceed bound {tabs}{nid}:[{fname}<{cond}] yes={left},no={right},missing={missing} {tabs} {cond} {left} {right} {missing} ,gain={loss_chg},cover={sum_hess} {loss_chg} {sum_hess} {tabs}{nid}:[f{fname}<{cond}] yes={left},no={right},missing={missing} Unknown feature map type. {tabs}{nid}:leaf={leaf}{stats} ,cover={cover} {leaf} {stats} {cover} {parent}{stat}
+{left}
+{right} {stat} {nodes} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "yes": {yes}, "no": {no}} {depth} "nodeid": {nid}, "depth": {depth}, "split": "{fname}", "split_condition": {cond}, "yes": {left}, "no": {right}, "missing": {missing} , "gain": {loss_chg}, "cover": {sum_hess} "nodeid": {nid}, "depth": {depth}, "split": {fname}, "split_condition": {cond}, "yes": {left}, "no": {right}, "missing": {missing} {{properties} {stat}, "children": [{left}, {right}
+{indent}]} {properties} { "nodeid": {nid}, "leaf": {leaf} {stat}} , "cover": {sum_hess} {newline}{indent}{nodes} {newline} yes_color #0000FF Edge color when meets the node condition. #FF0000 Edge color when doesn't meet the node condition. rankdir Passed to graphiz via graph_attr. condition_node_params Conditional node configuration leaf_node_params Leaf node configuration graph_attrs Any other extra attributes for graphviz `graph_attr`. Failed to parse graphviz parameters:
+ " graph [ {key}="{value}" ]
+ {key} {value} The following parameters for graphviz are not recognized:
+ ch == '{' , Expect '{' but get ' , JSON object expect '}' or ',' ' ch == ':' , Expect ':' but get ' ch == '\"' , Expect '"' but get ' unknown string escape \ , Expect '"' but reach end of line {nid} [ label="{fname}{<}{cond}" {params}]
+ {<} < {nid} -> {child} [label="{is_missing}" color="{color}"]
+ {child} {color} {is_missing} yes, missing no {nid} [ label="leaf={leaf-value}" {params}]
+ {leaf-value} {parent}
+{left}
+{right} digraph {
+ graph [ rankdir={rankdir} ]
+{graph_attrs}
+{nodes}} {rankdir} {graph_attrs} /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/tree_updater.cc Unknown tree updater ColMakerTrainParam grow_colmaker Grow tree with parallelization over columns. Distributed column split version of tree maker. opt_dense_col EXP Param: speed optimization for dense column. train_param colmaker_train_param /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/updater_colmaker.cc Updater `grow_colmaker` or `exact` tree method doesn't support distributed training. seed feat_set.size() == num_features Check failed: param_.cache_opt Support for `cache_opt' is removed in 1.0.0 fmat.Info().num_row_ == position_.size() /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/../common/random.h features.size() > 0 /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/include/xgboost/tree_model.h Check failed: node.IsLeaf() param.num_nodes < std::numeric_limits<int>::max() number of nodes in the tree exceed 2^31 ridx < position_.size() ridx exceed bound ridx= pos= prune trees.size() == 1U DistColMaker: only support one tree at a time Check failed: !tree[nid].IsLeaf() inconsistent reduce information nid >= 0 grow_local_histmaker Tree constructor that uses approximate histogram construction. grow_histmaker Tree constructor that uses approximate global of histogram construction. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/../common/quantile.h /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/updater_histmaker.cc Check failed: param_.max_depth > 0 max_depth must be larger than 0 node2workindex_[nid] == static_cast<int>(wid) summary_array_.size() == sketchs_.size() offset == -2 this->wspace_.rptr.size() == (fset.size() + 1) * this->qexpand_.size() + 1 /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/./updater_basemaker-inl.h fid * 2 + 1 < fminmax_.size() FeatHelper fid exceed query bound /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/param.h ret > 0U Check failed: tree[nid].IsLeaf() sketch->temp.size < max_size invalid maximum size max_size= , stemp.size INFO: rmax= , sum_total= , naxt_goal= , size= sketch->temp.size <= max_size Finalize: invalid maximum size, max_size= , stemp.size= fid * 2 < fminmax_.size() fv= , hist.size= hist[ ]= , hist.last= istart != hist.size this->qexpand_.size() == 1U this->wspace_.rptr.back() == this->wspace_.cut.size() Pruner that prune the tree according to statistics. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/updater_prune.cc tree pruning end, extra nodes, pruned nodes, max_depth= Check failed: nodes_[nodes_[rid].LeftChild() ].IsLeaf() Check failed: nodes_[nodes_[rid].RightChild()].IsLeaf() nid >= 1 SyncHistograms AddHistRows BuildLocalHistograms BuildNodeStats Update UpdatePredictionCache /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.cc out_preds.size() > 0U Check failed: (*p_last_tree_)[nid].IsLeaf() Check failed: (param_.max_depth > 0 || param_.max_leaves > 0) max_depth or max_leaves cannot be both 0 (unlimited); at least one should be a positive quantity. max_depth cannot be 0 (unlimited) when grow_policy is depthwise. min_nbins_per_feature > 0U EvaluateSplit ApplySplit upper_bound < static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) InitNewNode grow_fast_histmaker (Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram. Grow tree using quantized histogram. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/../common/column_matrix.h gmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_val /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/../common/hist_util.h Check failed: ptr Failed to allocate memory Quantile::Builder row_ptr_[nid] != kMax SubtractionTrick row_ptr_[nid] == kMax nodes == targeted_hists.size() /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/../common/threading_utils.h i < first_dimension_.size() hist_total == hist_memory_.size() /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/../common/row_set.h Check failed: e.begin != nullptr access element that is not in the set elem_of_each_node_.size() == 0U begin < end end > begin nid < nodes_ i < ranges_.size() tid < nthreads_ cut_ptr[fid] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) cut_ptr[fid + 1] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) grow_fast_histmaker is deprecated, use grow_quantile_histmaker instead. refresh Refresher that refreshes the weight and statistics according to data. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/updater_refresh.cc batch.Size() < std::numeric_limits<unsigned>::max() grow_skmaker Approximate sketching maker. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/src/tree/updater_skmaker.cc qexpand_.size() != 0U Syncher that synchronize the tree in all distributed nodes. LibSVMParserParam LibFMParserParam CSVParserParam libfm format File format indexing_mode If >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_column Column index (0-based) that will put into label. delimiter Delimiter used in the csv file. weight_column Column index that will put into instance weights. /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/disk_row_iter.h Check failed: TryLoadCache() failed to build cache file /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./row_block.h Check failed: fi->Read(&label) Bad RowBlock format Check 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/sec finish reading at %g MB/sec batch.field[i] <= std::numeric_limits<IndexType>::max() field exceed numeric bound of current type batch.index[i] <= std::numeric_limits<IndexType>::max() index exceed numeric bound of current type label.size() + 1 == offset.size() offset.back() == index.size() Check failed: offset.back() == value.size() || value.size() == 0 /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.h finish reading at /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data.cc Unknown data type /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.h param_.format == "libsvm" /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./text_parser.h chunk.size != 0U qid: Check failed: out->label.size() + 1 == out->offset.size() Check failed: base <= 10 && base >= 2 sign == true /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.h cannot call ParseNext /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/libfm_parser.h param_.format == "libfm" Check failed: out->field.size() == out->index.size() /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/csv_parser.h param_.format == "csv" Check failed: param_.label_column != param_.weight_column || param_.label_column < 0 Must have distinct columns for labels and instance weights Delimiter ' ' is not found in the line. Expected ' ' as the delimiter to separate fields. Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size() file:// hdfs:// viewfs:// /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io.cc Please compile with DMLC_USE_HDFS=1 to use hdfs s3:// http:// https:// Please compile with DMLC_USE_S3=1 to use S3 azure:// Please compile with DMLC_USE_AZURE=1 to use Azure unknown filesystem protocol stdin Check failed: part < nsplit invalid input parameter for InputSplit::Create indexed_recordio need to pass index file to use IndexedRecordIO recordio unknown input split type .split .part /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/uri_spec.h name_cache.size() == 1U only one `#` is allowed in file path for cachefile specification Check failed: std::getline(is, kv.first, '=') Invalid uri argument format for key in arg Check failed: std::getline(is, kv.second) for value in arg name_args.size() == 1U rb /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/single_file_split.h Check failed: fp_ != NULL SingleFileSplit: fail to open Check failed: part_index == 0 && num_parts == 1 InputSplit do not support write :// /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/cached_input_split.h Check failed: nread == sizeof(size) has invalid cache file format Check failed: fi_->Read(p->begin, size) == size BeforeFirst is not supported Check failed: this->InitCachedIter() Failed to initialize CachedIter ResetPartition is not supported in CachedInputSplit /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.cc Check failed: begin != end /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/recordio_split.cc Check failed: fi->Read(&lrec, sizeof(lrec)) != 0 invalid record io format (reinterpret_cast<size_t>(begin) & 3UL) == 0U (reinterpret_cast<size_t>(end) & 3UL) == 0U Check failed: p >= pbegin + 2 Check failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->end Invalid RecordIO Format (reinterpret_cast<size_t>(chunk->begin) & 3UL) == 0U (reinterpret_cast<size_t>(chunk->end) & 3UL) == 0U Check failed: chunk->begin <= chunk->end Check failed: cflag == 1U Check failed: p[0] == RecordIOWriter::kMagic /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.cc expanded_list.size() == 1ul IndexedRecordIOSplitter does not support multiple index files /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/input_split_base.cc Check failed: files_[i].size % align_bytes == 0 file do not align by bytes Check 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 needed files_.size() != 0U Cannot find any files that matches the URI pattern curr= ,begin= ,end= ,fileptr= ,fileoffset= offset[ file offset not calculated correctly /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/filesys.cc Check failed: !IsSymlink(info.path.name) Symlink not supported in TemporaryDirectory Couldn't remove file ; you may want to remove it manually Successfully deleted temporary directory ~TemporaryDirectory(): Could not remove temporary directory /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/filesystem.h lstat(path.c_str(), &sb) == 0 dmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes /Users/runner/runners/2.165.2/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/local_filesys.cc LocalFileSystem.GetPathInfo: detected symlink error: LocalFileSystem.GetPathInfo: LocalFileSystem.ListDirectory .. stdout wb Check failed: allow_null LocalFileSystem::Open " ": Check failed: std::fwrite(ptr, 1, size, fp_) == size FileStream.Write incomplete Check failed: !std::fseek(fp_, static_cast<long>(pos), SEEK_SET) NULL worker rabit_reduce_buffer 256MB DMLC_TASK_ID DMLC_ROLE DMLC_NUM_ATTEMPT DMLC_TRACKER_URI DMLC_TRACKER_PORT DMLC_WORKER_CONNECT_RETRY DMLC_WORKER_STOP_PROCESS_ON_ERROR %[^=]=%s mapred_tip_id mapreduce_task_id hadoop_mode is set but cannot find mapred_task_id rabit_task_id rabit_hadoop_mode mapred_task_id %d rabit_num_trial mapred_map_tasks mapreduce_job_maps hadoop_mode is set but cannot find mapred_map_tasks rabit_world_size Rabit Module currently only work with dmlc worker, quit this program by exit 0
+ can only call Init once start failed to shutdown due to %s
+ %s print rabit_tracker_uri rabit_tracker_port rabit_reduce_ring_mincount rabit_reduce_ring_mincount should be greater than 0 invalid value of DMLC_WORKER_STOP_PROCESS_ON_ERROR rabit_debug rabit_timeout rabit_timeout_sec rabit_timeout_sec should be non negative second rabit_enable_tcp_no_delay connect to (failed): [%s]
+ Connect retry connect to ip(retry time %d): [%s]
+ ReConnectLink failure 1 ReConnectLink failure 2 sync::Invalid tracker message, init failure ReConnectLink failure 3 task %s connected to the tracker
+ ReConnectLink failure 4 must keep rank to same if the node already have one task %s got new rank %d
+ ReConnectLink fail to bind the ports specified ReConnectLink failure 5 ReConnectLink failure 6 ReConnectLink failure 7 ReConnectLink failure 8 ReConnectLink failure 9 ReConnectLink failure 10 ReConnectLink failure 12 ReConnectLink failure 13 ReConnectLink failure, link rank inconsistent Override a link that is active ReConnectLink failure 14 ReConnectLink failure 15 ReConnectLink: bad socket cannot find parent in the link cannot find prev ring in the link cannot find next ring in the link failed in ReconnectLink %s
+ buffer size inconsistent must assign buffer_size Allreduce: size check Allreduce: boundary error Broadcast: root should be smaller than world size need to assume rank structure write ptr boundary check [%d] read_ptr boundary check fail to get host name Socket::Close double close the socket or close without create error during send SendStr %lu%c invalid format for %s invalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB} Create cannot obtain address of %s Does not support IPv6 Socket %s Error:%s SendAll RecvAll 0.0.0.0 TryBindHost GetSockError error during send RecvStr Accept SetNonBlock-1 SetNonBlock-2 SetKeepAlive too large type_nbytes=%lu, buffer_size=%lu Poll ReadToRingBuffer: buffer not allocated ReadToRingBuffer: max_size_read check Allreduce: boundary check AllgatherRing failed Allreduce failed Broadcast failed InitAfterException: not implemented rabit_global_replica rabit_local_replica [EXPERIMENTAL] bootstrap cache has been enabled
+ Shutdown: check point must return true Shutdown: check ack must return true expect timeout task return
+ %s
+ can't set empty cache cur_cache_seq is smaller than lookup cache seq index cache size stored expected to be same as requested cache size should be greater than 0 :: # [%d] allgather (%s) finished version %d, seq %d, take %f seconds
+ x [%d] allreduce (%s) finished version %d, seq %d, take %f seconds
+ @ [%d] broadcast (%s) root %d finished version %d,seq %d, take %f seconds
+ need to set rabit_local_replica larger than 1 to checkpoint local_model [%d] local model inconsistent, nlocal=%d read in version number local model inconsistent, nlocal=%d check ack must return true no need to load cache
+ [%d] loadcheckpoint size %ld finished version %d, seq %d, take %f seconds
+ [%d] loadcheckpoint reset
+ Can only call Checkpoint/LoadCheckPoint always withor without local_model, but not mixed case check point must return true [%d] checkpoint finished version %d,seq %d, take %f seconds
+ [%d] checkpoint ack finished version %d, take %f seconds
+ must already gone bad wrong oob msg should already read past mark BUG wrong Ack MSG must know the error link [EXPERIMENTAL] timeout thread expires in %d second(s)
+ recover [%d] Allreduce size inconsistent, distin=%lu, size=%lu, reporting=%lu
+ Too many nodes went down and we cannot recover.. cannot get and receive request request result inconsistent TryRecoverData TryDecideRouting recv_link must be active boundary check requester is expected to have fewer cache entries LoadCheckPoint: too many nodes fails, cannot recover local state TryGetResult::Checkpoint zero size check point is not allowed Allreduce 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 VersionNumber must only set seqno for normal operations pass negative seqno flag version check ack & check pt cannot occur together with normal ops min seq bug checkpoint req checkpoint act checkpoint node should be KHaveData role buf should have data from resbuf buf size should be greater than 0 checkpoint with kSpecialOp loadcache req loadcache act load cache state expect no nodes doing load checkpoint load cache state expect no nodes doing checkpoint load cache state expect no nodes doing checkpoint ack load cache not interacte with rest states local chkpt space inconsistent invalid local replica TryCheckinLocalState must have exactly 1 state RingPassing: boundary check1 RingPassing: boundary check2 RingPassing: boundary check3 cannot allocate 0 size memory PushTemp seqid inconsistent PushTemp inconsistent failed to get time there is nothing to be dropped reporter:status:Rabit Phase[%03d] Operation %03d
+ [%d] %s - |%lu|%d|%d|%d|%d| - |%lu|%d|
+ [%d] timeout thread %ld starts
+ [%d] timeout task thread %ld exits
+ [%d] exit due to time out %d s
+ parent must be 0 invalie stage id invalid stage MsgPassing invalid stage the rabit has not been initialized cannot initialize reduce handle twice must intialize handle to call AllReduce unknown enum_op unknown data_type %s, shutting down process
+ %s, rabit is configured to keep process running
+ Read pickle string not implemented DataType does not support bitwise or operation L P XQ ! QaQ QX ! Qa Q 9 % < 4 L , @ \ , ; 9 4L # `L & L + M , PM , M p. M / N @1 TN 2 N 4 N ; O > O ? 8P A P B P E DQ 0F Q `H Q pJ XR `L R pM S N LS `P S `Q S @T <T W T [ U \ \U ^ U e 8V h V o tW pp W s W u W { X | X @ 4Y Y Y 0 $Z lZ P Z ` Z Z [ d[ [ [ ` \ \ л \ ] $] @] 0 X] ] ] ` ,^ @ D^ \^ ^ ^ ^ _ ` 4_ L_ t_ _ _ _ (` l` P ` ` ` `
+ `
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- Const 1DeviceCanAccessEiNS_9GPUAccessE 4 DeviceSpanEi 2HostVectorEv 3
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linear Ĭmetric Metric6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE 1 9DenseCuts 21 8CopyHistENS0_4SpanINS_4tree9GradStatsELm18446744073709551615EEES4_mm 7Monitor p 2G 4AllVisibleGPUsEv 3 0SparseCuts 1CutsBuilder8UseGroupEPNS_7DMatrixE 6 5 8LoadSequentialFileENSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE W lobalRandomEv HistBuilder Ў HistogramCuts IncrementHistENS0_4SpanINS_4tree9GradStatsELm18446744073709551615EEES4_mm C 5BuildEPNS_7DMatrixEj 2Ev 1Ev 5BuildEPNS_7DMatrixEj 1 6ConcatERKNSt3__16vectorINS2_10unique_ptrIS1_NS2_14default_deleteIS1_EEEENS2_9allocatorIS7_EEEEj 5BuildEPNS_7DMatrixEj 4InitEPNSt3__16vectorINS0_16WXQuantileSketchIffEENS2_9allocatorIS5_EEEEj 7SingleThreadBuildERKNS_10SparsePageERKNS_8MetaInfoEjbjjj 1LoadBalanceERKNS_10SparsePageEm І GHistIndexMatrix4InitEPNS_7DMatrixEi PeekableInStream T GHistIndexBlockMatrix4InitERKNS0_16GHistIndexMatrixERKNS0_12ColumnMatrixERKNS_4tree10TrainParamE InitilizeHistByZeroesENS0_4SpanINS_4tree9GradStatsELm18446744073709551615EEEmm SubtractionHistENS0_4SpanINS_4tree9GradStatsELm18446744073709551615EEES4_S4_mm FixedSizeStream U 9BuildHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS2_9allocatorIS6_EEEENS0_16RowSetCollection4ElemERKNS0_16GHistIndexMatrixENS0_4SpanINS_4tree9GradStatsELm18446744073709551615EEE 1 4BuildBlockHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS2_9allocatorIS6_EEEENS0_16RowSetCollection4ElemERKNS0_21GHistIndexBlockMatrixENS0_4SpanINS_4tree9GradStatsELm18446744073709551615EEE 6SubtractionTrickENS0_4SpanINS_4tree9GradStatsELm18446744073709551615EEES5_S5_ 2 1 6engine 5 1SerializeReducerFunc_IN7xgboost6common22QuantileSketchTemplateIffNS2_10WXQSummaryIffEEE16SummaryContainerEEEvPKvPviRKN3MPI8DatatypeE 2SerializeReduceClosureIN7xgboost6common22QuantileSketchTemplateIffNS2_10WXQSummaryIffEEE16SummaryContainerEE6InvokeEPv op7ReducerINS0_ s 6 0 W5 Y1 e7Learner 3 8ConsoleLoggerParam11__MANAGER__Ev 4UnwoundPathSumEPKNS_11PathElementEjj HostDeviceVectorI GenericParameter fE NS_ (iE 0yE ?jE FmE M C D !aSEOS1_ !1 #4 &6ResizeEmf ( 2E 1E mfi St16initializer_listIfEi !RKNSt3__16vectorIfNS2_9allocatorIfEEEEi !OS1_ ! mfi !St16initializer_listIfEi !RKNSt3__16vectorIfNS2_9allocatorIfEEEEi !OS1_ ! Н 2Ev !1Ev ! 7xgboost "5rabit6engine13AllreduceBase14ConnectTrackerEv 1 "5Value7TypeStrEv Y9JsonArrayeqERKNS_5ValueE d8 k6common7Monitor r4 3gbm 7 6HostDeviceVectorI #0 _1Json h fE #NS_ +iE 2yE AjE HmE P 4SizeEv #9 #1 $ DeviceIdxEv #SetDeviceEi ( 0 $3DevicePointerEv %1HostPointerEv & DeviceSpanEv $HostVectorEv & 5Const %0 %8ConstDevicePointerEv %3Device %6ConstHostPointerEv &1Host &2 '4DeviceCanWriteEv ( DeviceSpanEv %HostVectorEv & DeviceSpanEv %HostVectorEv ' PointerEv &CanReadEv ( Ц PointerEv &CanReadEv ' FillEf &CopyE & RK 'St16initializer_listIfE ' S1_ 'NSt3__16vectorIfNS2_9allocatorIfEEEE ' а HostCanWriteEv 'DeviceAccessEv (к 6detail20GradientPairInternalIfEEE (5EntryEE 7 C (D *aSEOS4_ +1 ,4 .6ResizeEmS3_ 0 2E )1E ) mS3_i )St16initializer_listIS3_Ei *RKNSt3__16vectorIS3_NS5_9allocatorIS3_EEEEi *OS4_ * mS3_i *St16initializer_listIS3_Ei *RKNSt3__16vectorIS3_NS5_9allocatorIS3_EEEEi *OS4_ + 2Ev *1Ev * 6detail20GradientPairInternalIfEEE +5EntryEE : 4SizeEv +9 +1 , DeviceIdxEv +SetDeviceEi 0 0 ,3DevicePointerEv .1HostPointerEv . DeviceSpanEv ,HostVectorEv . 5Const -0 -8ConstDevicePointerEv .3Device .6ConstHostPointerEv .1Host .2 /4DeviceCanWriteEv 0 DeviceSpanEv -HostVectorEv . DeviceSpanEv -HostVectorEv / PointerEv .CanReadEv 0 PointerEv .CanReadEv / FillES3_ .CopyE / RK /St16initializer_listIS3_E / S4_ /NSt3__16vectorIS3_NS5_9allocatorIS3_EEEE / HostCanWriteEv 0DeviceAccessEv 0 C 0D 2aSEOS1_ 21 34 66ResizeEmi 7 2E 01E 1 mii 1St16initializer_listIiEi 2RKNSt3__16vectorIiNS2_9allocatorIiEEEEi 2OS1_ 2 mii 2St16initializer_listIiEi 2RKNSt3__16vectorIiNS2_9allocatorIiEEEEi 2OS1_ 2 2Ev 21Ev 2 4SizeEv 29 31 3 DeviceIdxEv 3SetDeviceEi 7 0 33DevicePointerEv 51HostPointerEv 5 DeviceSpanEv 3HostVectorEv 5 5Const 40 58ConstDevicePointerEv 53Device 56ConstHostPointerEv 51Host 52 74DeviceCanWriteEv 7 DeviceSpanEv 5HostVectorEv 5 DeviceSpanEv 5HostVectorEv 6 PointerEv 5CanReadEv 7 PointerEv 6CanReadEv 7 FillEi 6CopyE 6 RK 6St16initializer_listIiE 7 S1_ 6NSt3__16vectorIiNS2_9allocatorIiEEEE 7
+ Ї
+ HostCanWriteEv 7DeviceAccessEv 7
+
+
+
+
+
+ C 8D 9aSEOS2_ :1 :4 =6ResizeEmS1_ ? 2E 81E 8 mS1_i 8St16initializer_listIS1_Ei 9RKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi 9OS2_ :
+ mS1_i 9St16initializer_listIS1_Ei 9RKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi 9OS2_ :
+
+ Џ
+
+
+ 2Ev :1Ev :
+
+
+
- RKNS_15GPUDistributionE 5NS_6GPUSetE 5
-
-
- C 5D 8aSERKS2_ 81 :4 <6ResizeEmS1_ > 2E 51E 6 mS1_RKNS_15GPUDistributionE 6St16initializer_listIS1_ERKNS_15GPUDistributionE 7RK 7
- mS1_RKNS_15GPUDistributionE 7St16initializer_listIS1_ERKNS_15GPUDistributionE 7RK 7
-
-
- NSt3__16vectorIS1_NS3_9allocatorIS1_EEEERKNS_15GPUDistributionE 7S2_ 8
- NSt3__16vectorIS1_NS3_9allocatorIS1_EEEERKNS_15GPUDistributionE 8S2_ 8
- 2Ev 81Ev 8
-
-
-
-
- 4SizeEv 97DevicesEv 91 95ShardE =
-
- 2DistributionEv 95 :0 ;8ConstDevicePointerEi ;3 ;6ConstHostPointerEv <1 <
- 0 :3DevicePointerEi ;1HostPointerEv < DeviceSpanEi :HostVectorEv <
- Const :DeviceCanAccessEiNS_9GPUAccessE = DeviceSpanEi ;HostVectorEv <
- DeviceS ;HostVectorEv = panEi ;izeEi <Ш
-
-
- DevicePointerEi <HostCanAccessENS_9GPUAccessE =
-
-
-
- Щ
- HostPointerEv <DeviceStartEi <
-
+ 4SizeEv :9 :1 ;
+ DeviceIdxEv :SetDeviceEi ?
+ 0 ;3DevicePointerEv <1HostPointerEv = DeviceSpanEv ;HostVectorEv =
+ 5Const <0 <8ConstDevicePointerEv <3Device <6ConstHostPointerEv =1Host =2 >4DeviceCanWriteEv ? DeviceSpanEv <HostVectorEv =
+ DeviceSpanEv <HostVectorEv >
+
+
+ PointerEv =CanReadEv >
+ И
+
+
+
+ PointerEv =CanReadEv >
+ FillES1_ =CopyE =
+ RK >St16initializer_listIS1_E > S2_ >NSt3__16vectorIS1_NS3_9allocatorIS1_EEEE >
+
+
- FillES1_ <CopyE =
- RK =St16initializer_listIS1_E = S2_ =NSt3__16vectorIS1_NS3_9allocatorIS1_EEEE =
-
-
-
-
-
- RKNS_15GPUDistributionE >NS_6GPUSetE >
-
- о
- C >D AaSERKS1_ A1 B4 E6ResizeEmm G 2E >1E ? mmRKNS_15GPUDistributionE ?St16initializer_listImERKNS_15GPUDistributionE @RK @
- mmRKNS_15GPUDistributionE @St16initializer_listImERKNS_15GPUDistributionE @RK @
-
-
- NSt3__16vectorImNS2_9allocatorImEEEERKNS_15GPUDistributionE @S1_ A
- NSt3__16vectorImNS2_9allocatorImEEEERKNS_15GPUDistributionE AS1_ A
- 2Ev A1Ev A
-
-
-
-
- 4SizeEv B7DevicesEv B1 B5ShardE F
-
- 2DistributionEv B5 C0 D8ConstDevicePointerEi D3 D6ConstHostPointerEv E1 E
- 0 C3DevicePointerEi D1HostPointerEv E DeviceSpanEi CHostVectorEv E
- Const CDeviceCanAccessEiNS_9GPUAccessE F DeviceSpanEi DHostVectorEv E
- DeviceS DHostVectorEv F panEi DizeEi E
-
-
- DevicePointerEi EHostCanAccessENS_9GPUAccessE F
-
-
-
-
- HostPointerEv EDeviceStartEi E
-
-
- FillEm ECopyE E
- RK FSt16initializer_listImE F S1_ FNSt3__16vectorImNS2_9allocatorImEEEE F
-
-
-
+
+ HostCanWriteEv >DeviceAccessEv ?
+
+ Э
+
+
+
+ C ?D AaSEOS1_ A1 B4 D6ResizeEmy F 2E ?1E @ myi @St16initializer_listIyEi ARKNSt3__16vectorIyNS2_9allocatorIyEEEEi AOS1_ AЮ
+ myi @St16initializer_listIyEi ARKNSt3__16vectorIyNS2_9allocatorIyEEEEi AOS1_ A
+
+
+
+
+ 2Ev A1Ev A
+
+
+
+
+ 4SizeEv A9 A1 B
+ DeviceIdxEv ASetDeviceEi F
+ 0 B3DevicePointerEv D1HostPointerEv D DeviceSpanEv BHostVectorEv Dп
+ 5Const C0 C8ConstDevicePointerEv D3Device D6ConstHostPointerEv D1Host D2 E4DeviceCanWriteEv F DeviceSpanEv CHostVectorEv D
+ DeviceSpanEv DHostVectorEv E
+
+
+ PointerEv DCanReadEv F
+
+
+
+
+ PointerEv DCanReadEv E
+ FillEy DCopyE E
+ RK ESt16initializer_listIyE E S1_ ENSt3__16vectorIyNS2_9allocatorIyEEEE E
+
+
+
+
+ HostCanWriteEv FDeviceAccessEv F
+
+
+
+
+
+ C FD HaSEOS1_ H1 I4 L6ResizeEmj M 2E F1E G mji GSt16initializer_listIjEi HRKNSt3__16vectorIjNS2_9allocatorIjEEEEi HOS1_ H
+ mji HSt16initializer_listIjEi HRKNSt3__16vectorIjNS2_9allocatorIjEEEEi HOS1_ H
+
+
+
+
+ 2Ev H1Ev H
+
+
+
+
+ 4SizeEv H9 I1 I
+ DeviceIdxEv ISetDeviceEi M
+ 0 I3DevicePointerEv K1HostPointerEv K DeviceSpanEv IHostVectorEv K
+ 5Const J0 K8ConstDevicePointerEv K3Device K6ConstHostPointerEv K1Host K2 M4DeviceCanWriteEv M DeviceSpanEv JHostVectorEv K
+ DeviceSpanEv KHostVectorEv L
+
+
+ PointerEv KCanReadEv M
+
- RKNS_15GPUDistributionE GNS_6GPUSetE G
-
-
- 8RegistryIN G1 l4data1 6 ڨ2io 7xgboost GS_16ParserFactoryRegI 4 H1 f9MetricRegEE3GetEv u data19SparsePageFormatRegEE3GetEv Htree17SplitEvaluatorRegEE3GetEv
- 5ClearEv I10LoadBinaryEPN4dmlc6StreamE I7SetInfoEPKcPKvNS_8DataTypeEm I Ё Ђ І DMatrix JLearner6CreateERKNSt3__16vectorINS1_10shared_ptrINS_7DMatrixEEENS1_9allocatorIS5_EEEE iRegTree1 4LoadERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEbbS9_m K6CreateE K15SaveToLocalFileERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE M ONSt3__110unique_ptrINS_10DataSourceENS1_14default_deleteIS3_EEEERKNS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE MPN4dmlc6ParserIjfEERKNSt3__112basic_stringIcNS5_11char_traitsIcEENS5_9allocatorIcEEEEm M Ы data Mtree 1 N49__dmlc_registry_file_tag_sparse_page_raw_format__Ev Z 6SparsePage O5SimpleCSRSource T3SimpleDMatrix W7SparsePageDMatrix X Format OSource ZWriter a 6CreateERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE P12DecideFormatERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE P SparsePage QExtendPathEPNS_11PathElementEjffi UnwindPathEPNS_11PathElementEjj 4PushERK Q7PushCSCERKS0_ Q S0_ QN4dmlc8RowBlockIjfEE Q 3 R5BitORE M RSumE s axE RinE yEEvPKvPviRKN3MPI8DatatypeE TjEEvPKvPviRKN3MPI8DatatypeE ifEEvPKvPviRKN3MPI8DatatypeE ɏcEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE
5ClearEv T8CopyFromEPN T1 U4NextEv W
S_7DMatrixE U4dmlc6ParserIjfEE U
0LoadBinaryEPN4dmlc6StreamE U1BeforeFirstEv V
data1 Utree14SplitEvaluator 5SimpleCSRSource V3SimpleDMatrix W7SparsePageDMatrix Y6SparsePageSource5ValueEv ^ 10SaveBinaryEPN4dmlc6StreamE V5ValueEv W 4InfoEv W1 W22GetSortedColumnBatchesEv X 4InfoEv W14SingleColBlockEv X 3Get X6GetColumnBatchesEv X ColDensityEm XRowBatchesEv X Ќ Ч 4InfoEv X1 Y22GetSortedColumnBatchesEv Y 4InfoEv Y14SingleColBlockEv Y 3Get Y6GetColumnBatchesEv Y RowBatchesEv YColDensityEm Y C [D \4NextEv \1 \5ValueEv ^21CreatePageFromDMatrixEPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEESC_m ` 2ERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_ \1ERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_ \ 2Ev \1Ev \0Ev \ й н 1BeforeFirstEv ^0CacheExistERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_ ^3CreateRowPageEPN ^6CreateColumnPageEPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEEb ` 4dmlc6ParserIjfEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEEm `S_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE ` 12ThreadedIterIN `4data14TextParserBaseI 7xgboost10SparsePageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ aS C bD c9PushWriteEONSt3__110shared_ptrINS_10SparsePageEEE d5AllocEPNSt3__110shared_ptrINS_10SparsePageEEE d 2ERKNSt3__16vectorINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEENS7_IS9_EEEESD_m c1ERKNSt3__16vectorINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEENS7_IS9_EEEESD_m c Ё 2Ev d1Ev d gbm dobj w 3 d1 e 5__dmlc_registry_file_tag_gblinear__Ev e3__dmlc_registry_file_tag_gbtree__Ev f 8GBLinear e6GBTree f4DartTrainParam11__MANAGER__Ev g ModelParam11__MANAGER__Ev eTrainParam11__MANAGER__Ev f 8GradientBoosterRegEE3GetEv f6LinearUpdaterRegEE3GetEv i4 {2PredictorRegEE3GetEv ModelParam11__MANAGER__Ev gTrainParam11__MANAGER__Ev g Learner gRegTree 19AllowLazyCheckPointEv h9DumpModelERKNS_10FeatureMapEbNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE h Э ModelParam11__MANAGER__Ev iTrainParam11__MANAGER__Ev i Ю LinearUpdater6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE jConsoleLogger mTrackerLoggerD o 1 j4 k 6LinearTrainParam11__MANAGER__Ev k5CoordinateParam11__MANAGER__Ev k 5__dmlc_registry_file_tag_updater_coordinate__Ev k2__dmlc_registry_file_tag_updater_shotgun__Ev l 6CustomLogMessage3LogERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE m2 Φ0 8TemporaryDirectory15RecursiveDeleteERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE D m9 n1 oC p6param_E 2Ev n1Ev o ShouldLogENS0_12LogVerbosityE oConfigureERKNSt3__13mapINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES8_NS1_4lessIS8_EENS6_INS1_4pairIKS8_S8_EEEEEE p 2Ev o1Ev o 6DefaultVerbosityEv p5GlobalVerbosityEv p7global_verbosity_E 2E p1E q NS0_12LogVerbosityE qRKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE r NS0_12LogVerbosityE rRKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE r 4 r11MetricParam11__MANAGER__Ev u3 u2 5__dmlc_registry_file_tag_elementwise_metric__Ev s4__dmlc_registry_file_tag_multiclass_metric__Ev u dEEvPKvPviRKN3MPI8DatatypeE ufEEvPKvPviRKN3MPI8DatatypeE wcEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE й 8__dmlc_registry_file_tag_rank_metric__Ev w5__make_MetricReg_PossionNegLoglik__E 2__make_MetricReg_GammaDeviance__E 1__make_MetricReg_ 3__make_MetricReg_TweedieNLogLik__E И! 3 w1 x41__dmlc_registry_file_tag_ y2 z 6__dmlc_registry_file_tag_hinge_obj__Ev x5__dmlc_registry_file_tag_rank_obj__Ev ~ " 3 y5LambdaRankParam11__MANAGER__Ev ~2RegLossParam11__MANAGER__Ev ~ HingeObjParam11__MANAGER__Ev yLambdaRankObj9ListEntry7CmpPredERKS2_S4_ ~ " multiclass_obj__Ev zregression_obj__Ev ~ # 2 z0GammaRegressionParam11__MANAGER__Ev ~ SoftmaxMultiClassParam11__MANAGER__Ev {PoissonRegressionParam11__MANAGER__Ev ~TweedieRegressionParam11__MANAGER__Ev ~ # ObjFunctionRegEE3GetEv {TreeUpdaterRegEE3GetEv Ӊ $ ObjFunction6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE ~DumpRegTreeERNSt3__118basic_stringstreamIcNS0_11char_traitsIcEENS0_9allocatorIcEEEERKNS_7RegTreeERKNS_10FeatureMapEiiibNS0_12basic_stringIcS3_S5_EE TreeUpdater6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE ى $ $ $ $ % % % % % predictor40__dmlc_registry_file_tag_cpu_predictor__Ev Predictor TreeParam11__MANAGER__Ev ن ( ) 4InitERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEERKNS2_INS1_10shared_ptrINS_7DMatrixEEENS7_ISH_EEEE ԁ6CreateENSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE ځ ) * Д* 1 2 4 ߉39__dmlc_registry_file_tag_updater_sync__Ev 4SplitEvaluator 6ElasticNetParams11__MANAGER__Ev 0TrainParam11__MANAGER__Ev ߆7QuantileHistMaker 6CreateERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 4InitERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE 5ResetEv 8AddSplitEjjjjff * * * * 17ComputeSplitScoreEjjRKNS0_9GradStatsES4_ ݅22CheckFeatureConstraintEjj * * * 5MonotonicConstraintParams11__MANAGER__Ev ͆7InteractionConstraintParams11__MANAGER__Ev ӆ * * , , , 9DumpModelERKNS_10FeatureMapEbNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE 2 ψ8TreeShapERKNS0_4FVecEPfjjPNS_11PathElementEffiijf lj , 8FillNodeMeanValuesEv È7FillNodeMeanValueEi Ɉ - - 8CalculateContributionsApproxERKNS0_4FVecEjPf 2CalculateContributionsERKNS0_4FVecEjPfij ͉ Ї- Ќ- - Ж- - - / / 3__dmlc_registry_file_tag_updater_colmaker__Ev ҋ4__dmlc_registry_file_tag_updater_histmaker__Ev 0__dmlc_registry_file_tag_updater_prune__Ev Տ8__dmlc_registry_file_tag_updater_quantile_hist__Ev ۏ2__dmlc_registry_file_tag_updater_ Τ / 2ReducerSafe_IN7xgboost4tree 3InvokeLambda_EPv Ϗ 1 ܌9GradStatsEXadL_ZNS3_6ReduceERS3_RKS3_EEEEvPKvPviRKN3MPI8DatatypeE Ï 0SplitEntryEXadL_ZNS3_6ReduceERS3_RKS3_EEEEvPKvPviRKN3MPI8DatatypeE 1SketchMaker7SKStatsEXadL_ZNS4_6ReduceERS4_RKS4_EEEEvPKvPviRKN3MPI8DatatypeE 1 jEEvPKvPviRKN3MPI8DatatypeE cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE 1 1 2 3 3 4 5 4InitERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE 6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEE 21UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE 7Builder 5 5 5 2 1 6UpdateERKNS_6common16GHistIndexMatrixERKNS3_21GHistIndexBlockMatrixERKNS3_12ColumnMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEPNS_7RegTreeE 8InitDataERKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS7_9allocatorISB_EEEERKNS_7DMatrixERKNS_7RegTreeE 9LossGuideENS2_11ExpandEntryES3_ 1UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE 0 Қ 5 4 1InitNewNodeEiRKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS7_9allocatorISB_EEEERKNS_7DMatrixERKNS_7RegTreeE 3EvaluateSplitEiRKNS_6common16GHistIndexMatrixERKNS3_14HistCollectionERKNS_7DMatrixERKNS_7RegTreeE 0ApplySplitEiRKNS_6common16GHistIndexMatrixERKNS3_12ColumnMatrixERKNS3_14HistCollectionERKNS_7DMatrixEPNS_7RegTreeE 9 SyncHistogramsEiiPNS_7RegTreeE ̚BuildNodeStatsERKNS_6common16GHistIndexMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSB_9allocatorISF_EEEE E 5 BuildLocalHistogramsEPiS3_RKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSD_9allocatorISH_EEEE ExpandWithDepthWidthERKNS_6common16GHistIndexMatrixERKNS3_21GHistIndexBlockMatrixERKNS3_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSH_9allocatorISL_EEEE ApplySplitSparseDataENS_6common16RowSetCollection4ElemERKNS3_16GHistIndexMatrixEPNSt3__16vectorINS4_5SplitENS9_9allocatorISB_EEEERKNS3_6ColumnEjjib Ȥ 5 5 5 valuateSplitsERKNS_6common16GHistIndexMatrixERKNS3_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS2_11ExpandEntryENSG_9allocatorISI_EEEE numerateSplitEiRKNS_6common16GHistIndexMatrixERKNS3_4SpanINS0_9GradStatsELxn1EEERKNS1_9NodeEntryERKNS_8MetaInfoEPNS0_10SplitEntryEjj 5 6 6 6 ExpandWithLossGuideERKNS_6common16GHistIndexMatrixERKNS3_21GHistIndexBlockMatrixERKNS3_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSH_9allocatorISL_EEEE ApplySplitDenseDataENS_6common16RowSetCollection4ElemERKNS3_16GHistIndexMatrixEPNSt3__16vectorINS4_5SplitENS9_9allocatorISB_EEEERKNS3_6ColumnEib ¤ 6 6 6 6 6 7 7 refresh__Ev skmaker__Ev 8 8 8 9 7 6LibFMParserParam11__MANAGER__Ev ¦4CSVParserParam11__MANAGER__Ev Ȧ8CreateLibSVMParserI 5CreateCSVParserI LibSVMParserParam11__MANAGER__Ev CreateLibFMParserI 9 9 9 RowBlockIterI ThreadedIterINS_2io14InputSplitBase5ChunkEE14NotImplementedEv j y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ ¨xE6CreateEPKcjjS3_ Ψ 9 fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ ȨxE6CreateEPKcjjS3_ Ԩ 9 9 : : : ParserI Stream6CreateEPKcS2_b j y ֩ fE6CreateEPKcjjS3_ ЩiE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ Г: fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ : : : : : j Īy fEEE3GetEv iEEE3GetEv xEEE3GetEv : : : fEEE3GetEv iEEE3GetEv xEEE3GetEv : : : jfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj yfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj ; Ј; jfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj yfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj ; ; j Ȱy fEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj iEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj xEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj ; fEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj iEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj xEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj ; ; ; ; ; 7_ _6vectorINS7_4data17RowBlockContainerI 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ j y fEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ iEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ ʼxEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ ּ< fEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ ļiEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ мxEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ ܼ= > ? @ B j y fE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjfEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ iE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjiEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ xE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjxEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ C jfEENS_9allocatorISC_EEEEE4InitENS_8functionIFbPPSF_EEENSH_IFvvEEEEUlvE_EEEEEPvSQ_ yfEENS_9allocatorISC_EEEEE4InitENS_8functionIFbPPSF_EEENSH_IFvvEEEEUlvE_EEEEEPvSQ_ C fE8FillDataEPNS_6vectorINS8_17RowBlockContainerIyfEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ iE8FillDataEPNS_6vectorINS8_17RowBlockContainerIyiEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ xE8FillDataEPNS_6vectorINS8_17RowBlockContainerIyxEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ D ОE G G H H 1 23IndexedRecordIOSplitter 0FileSystem 2LineSplitter1 6RecordIOSplitter1 4InputSplitBase 5LocalFileSystem 11GetInstanceERKNS0_3URIE 22ListDirectoryRecursiveERKNS0_3URIEPNSt3__16vectorINS0_8FileInfoENS5_9allocatorIS7_EEEE H InputSplit6CreateEPKc SeekStream13CreateForReadEPKcb jjS2_ S2_jjS2_bimb H H I ЄI J J 5SeekRecordBeginEPNS_6StreamE 9FindLastRecordBeginEPKcS3_ 7ExtractNextRecordEPNS_10InputSplit4BlobEPNS0_14InputSplitBase5ChunkE J J J 5SeekRecordBeginEPNS_6StreamE 9FindLastRecordBeginEPKcS3_ 7ExtractNextRecordEPNS_10InputSplit4BlobEPNS0_14InputSplitBase5ChunkE J J J 1 9 4ResetPartitionEjj 3ReadIndexFileEPNS0_10FileSystemERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE 5SeekRecordBeginEPNS_6StreamE 9FindLastRecordBeginEPKcS3_ 7ExtractNextRecordEPNS_10InputSplit4BlobEPNS0_14InputSplitBase5ChunkE 1 J J J J K ReadChunkEPvPm Next K ChunkEPNS_10InputSplit4BlobE BatchEPNS_10InputSplit4BlobEm K NextBatchExEPNS0_14InputSplitBase5ChunkEm BeforeFirstEv K K K 4 1 D 8StripEndENSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEc 9ReadChunkEPvPm 5Chunk InitEPNS0_10FileSystemEPKcmb ReadEPvm ОK 7InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb 4ResetPartitionEjj 1BeforeFirstEv 3ConvertToURIsERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 6ExtractNextChunkEPNS_10InputSplit4BlobEPNS1_5ChunkE ФK K K 2Ev 1Ev 0Ev K K K K K K K 4LoadEPS1_m 6AppendEPS1_m K K K O O 1 4OpenERKNS0_3URIEPKcb 1 3ListDirectoryERKNS0_3URIEPNSt3__16vectorINS0_8FileInfoENS5_9allocatorIS7_EEEE GetPathInfoERKNS0_3URIE OpenForReadERKNS0_3URIEb O O O O 1 4InitEiPPc 8FinalizeEv 9GetEngineEv 3AllreduceBase 5AllreduceRobust 2 1DataRequestERKNSt3__14pairIbiEERKNS1_6vectorIcNS1_9allocatorIcEEEEm 0Allreduce_EPvmmPFvPKvS1_iRKN3MPI8DatatypeEENS0_3mpi8DataTypeENSA_6OpTypeEPFvS1_ES1_ C 4InitEiPPc 1 8S 20TryReduceScatterRingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE 2Ev 1Ev O P P 4ReConnectLinksEPKc 2Tr 6TryAll P hutdownEv etParamEPKcS3_ P P ackerPrintERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE y P P AllreduceEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE BroadcastEPvmi P reduce gatherRingEPvmmmm RingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE TreeEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE P P Q Q Q C 4InitEiPPc 8S 1 9 20Try 2Ev 1Ev Q Q Q hutdownEv etParamEPKcS3_ Q 1 5 4 3 6TryDecideRoutingENS1_11RecoverTypeEPmPiPNSt3__16vectorIbNS5_9allocatorIbEEEE 7TryLoadCheckPointEb 2TryGetResultEPvmib R CheckPoint_EPKN4dmlc12SerializableES5_b ecoverExecEPvmii ingPassingEPvmmmmPNS0_13AllreduceBase10LinkRecordES5_ Q Q AllreduceEPvmmPFvPKvS2_iRKN3MPI8DatatypeEEPFvS2_ES2_ BroadcastEPvmi R CheckAndRecoverENS0_13AllreduceBase10ReturnTypeE LocalModelCheckEb R R LoadCheckPointEPN4dmlc12SerializableES4_ TryRecoverDataENS1_11RecoverTypeEPvmiRKNSt3__16vectorIbNS4_9allocatorIbEEEE R R R CheckinLocalStateEPNSt3__16vectorImNS2_9allocatorImEEEEPNS2_12basic_stringIcNS2_11char_traitsIcEENS4_IcEEEE RecoverLocalStateEPNSt3__16vectorImNS2_9allocatorImEEEEPNS2_12basic_stringIcNS2_11char_traitsIcEENS4_IcEEEE R TryResetLinksEv ActionSummary7ReducerEPKvPviRKN3MPI8DatatypeE R R ShortestDistERKNSt3__14pairIbmEERKNS1_6vectorINS2_IimEENS1_9allocatorIS7_EEEEm ReduceHandle R S S S S S S S T T T T C D 8TypeSizeERKN3MPI8DatatypeE 4InitEPFvPKvPviRKN3MPI8DatatypeEEm 9AllreduceEPvmmPFvS2_ES2_ 2Ev 1Ev ЍT T 2Ev 1Ev T T T T T I Finalize Get TrackerPrint Broadcast Allreduce L CheckPoint VersionNumber nit sDistributed T ЗT Rank WorldSize ProcessorName T T T T T T T oadCheckPoint inkTag T T T T T T T T T T cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE T T T T T T T T T T T T T T T T T T T S I VN N ZN PF F 4dmlc 7xgboost St3__1 5rabit 5ErrorE 6 8DataIterIN 1 7istream 9parameter1 4data ԝ2io Ѻ[ 1 6 7 4 3 9 4NativeDataIterE 0DataSourceE 7BatchIteratorImplE 5GradientBoosterE ݄1 ȅ3LinearUpdaterE [ ParserI StreamE j y fEE iEE xEE ѕ[ S 7xgboost10SparsePageEEE _ t3__16vectorINS_4data17RowBlockContainerI 8RowBlockI 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEE j y fEEEE iEEEE xEEEE [ [ [ 1 2 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-9basic_ 5 4default_deleteIN 7 0__ 8 1__ 3__empty_stateIcEE 6__ 2__match_charIcEE ostringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE istringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE Ȗ[ basic_stringbufIcNS_11char_traitsIcEENS_9allocatorIcEEEE __ [ 5 6engine utils1 c_api1 9MemoryFixSizeBufferE 8MemoryBufferStreamE З[ 0 2 SeekStreamE ParamErrorE InputSplitE [ [ [ E 5InBufE [ ʘ[ 0__ 3__match_any_but_newlineIcEE 8__begin_marked_subexpressionIcEE 6__end_marked_subexpressionIcEE 1__empty_non_own_stateIcEE shared_ptr_ match_char_collateIcNS_12regex_traitsIcEEEE bracket_expressionIcNS_12regex_traitsIcEEEE pointerIPN emplaceIN7xgboost16HostDeviceVectorIiEENS_9allocatorIS3_EEEE 7xgboost S_13__empty_stateIcEENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 7DMatrixENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 10SparsePageENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE [ 7xgboost S_13__empty_stateIcEEEE 7DMatrixEEE 10SparsePageEEE [ common1 linear metric MetricE 3HistCutMatrixE 6PeekableInStreamE [ DMatrixE LearnerE [ [ [ 0FieldEntryI 7FieldEntryNumericINS0_10FieldEntryI 4FieldEntryBaseINS0_10FieldEntryI 6FieldAccessEntryE iEE jEE NSt3__1 fEE mEE bEE dEE [ iEEiEE jEEjEE fEEfEE mEEmEE dEEdEE [ iEEiEE jEEjEE NSt3__1 fEEfEE mEEmEE bEEbEE dEEdEE Ɠ[ [ ן[ bad_function_callE __ [ data tree 1 23S 5SimpleCSRSourceE 3SimpleDMatrixE 7SparsePageDMatrixE 9SparsePageRawFormatE 6SparsePage [ [ impleBatchIteratorImplE parseBatchIteratorImplE Ǡ[ [ [ [ function6__ l_anchorIcEE r_anchorIcEE back_refIcEE baseIF funcI PN7xgboost b vvEEE 4 1 6MetricEPKcEEE 9PredictorEvEEE data16SparsePageFormatEvEEE tree14SplitEvaluatorENS_10unique_ptrIS4_NS_14default_deleteIS4_EEEEEEE Т[ [ FormatE SourceE [ [ ThreadedIterIN SerializableE RowBlockIterI מ 7xgboost10SparsePageEEE S [ PPN N7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES6_EEE 7xgboost10SparsePageEEEE 4dmlc ̢S_6vectorIN4dmlc4data17RowBlockContainerI ´[ [ [ Ī[ [ [ Ѭ[ 12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEEE 6vectorIiNS2_9allocatorIiEEEEEE [ 12basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEEEES9_EE 6vectorIiNS3_9allocatorIiEEEEEES7_EE [ [ [ ¯[ [ [ ذ[ 5GradientBoosterERKNS_6vectorINS_10shared_ptrINS2_7DMatrixEEENS_9allocatorIS8_EEEEfEEE 3LinearUpdaterEvEEE 1 [ gbm obj 8GBLinearE ׄ6GBTreeE 4DartE
[ [ basic_stringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE __ س[ [ Ҷ[ [ [ LearnerImplE ObjFunctionE TreeUpdaterE [ [ [ [ 1 2 7CoordinateUpdaterE 5FeatureSelectorE ·4ShotgunUpdaterE ƿ[ [ 1 2 ԇ CyclicFeatureSelectorE ȇGreedyFeatureSelectorE RandomFeatureSelectorE [ [ ShuffleFeatureSelectorE ThriftyFeatureSelectorE [ [ [ [ [ [ 1 ݈7Eval 9EvalAucPRE ͌8EvalNDCGE ߌ 3Eval 4EvalM 6EvalMultiLogLossE 2EvalRankListE ٌ EWiseBaseINS0_ PrecisionE ӌ 1 20EvalPoissonNegLogLikEEE 9EvalErrorEEE 1EvalRowRMSEEEE 0EvalRowMAEEEE 4EvalRowLogLossEEE 7EvalGammaDevianceEEE 6EvalGammaNLogLikEEE 8EvalTweedieNLogLikEEE [ [ [ [ [ [ [ [ [ atchErrorE ҋClassBaseINS0_1 ؋[ 4EvalMatchErrorEEE 6EvalMultiLogLossEEE [ [ [ A MAPE CoxE MSE ucE nj[ [ [ [ [ [ [ [ ObjFunctionEvEEE TreeUpdaterEvEEE ̓[ 8HingeObjE э20SoftmaxMultiClassObjE ݍ1 [ [ [ 5 3 Ύ7 6LambdaRankObjMAPE ď0RegLossObjINS0_ ʏ PairwiseRankObjE ȎGammaRegressionE ې[ LambdaRankObjE CoxRegressionE Ր[ LambdaRankObjNDCGE PoissonRegressionE ϐTweedieRegressionE [ [ 1 22LogisticClassificationEEE Ð 6LinearSquareLossEEE 8LogisticRegressionEEE 1LogisticRawEEE ɐ[ [ [ [ [ [ [ [ [ predictor12CPUPredictorE PredictorE [ [ 1 Ñ2 8ColMaker ғ9 ֔ 4SplitEvaluatorE 0 9MonotonicConstraintE 2DistColMaker 1 7QuantileHistMaker 3TreeRefresherE [ [ ElasticNetE TreePrunerE [ [ [ [ 1InteractionConstraintE 3GlobalProposalHistMakerE [ [ [ [ [ E 7BuilderE [ [ \ \ E 7BuilderE \ \ CQHistMakerE ДSketchMakerE ȝTreeSyncherE Νσ\ HistMakerE BaseMakerE \ \ ZN PF 7xgboost4tree1 4dmlc Ѡ 1CQHistMaker10CreateHistERKNS_6vectorINS2_6detail20GradientPairInternalIfEENS_9allocatorIS8_EEEEPNS2_7DMatrixERKNS5_IjNS9_IjEEEERKNS2_7RegTreeEEUlvE_NS9_ISN_EEFvvEEE 3TreeRefresher6UpdateEPNS2_16HostDeviceVectorINS2_6detail20GradientPairInternalIfEEEEPNS2_7DMatrixERKNS_6vectorIPNS2_7RegTreeENS_9allocatorISF_EEEEEUlvE_NSG_ISL_EEFvvEEE \ 7xgboost4tree1 4dmlc 1CQHistMaker10CreateHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS2_9allocatorIS6_EEEEPNS_7DMatrixERKNS3_IjNS7_IjEEEERKNS_7RegTreeEEUlvE_ 3TreeRefresher6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEEEUlvE_ \ \ \ 7BuilderE E \ \ bN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES6_ENS_9allocatorIS8_EES7_EE vvENS_9allocatorIS3_EES2_EE ߋ\ ь\ bN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_E vvE \ bN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_E vvE \ \ \ \ \ \ 1 9CSVParserI 1 2 4T ܰ0ParserImplI DiskRowIterI LibFMParserI j y ޥ fEE ўiEE xEE \ j y fEE iEE xEE \ _ t3__16vectorINS_4data17RowBlockContainerI 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEE j y fEEEE iEEEE xEEEE ٗ\ j y ަ fEEEE ˠiEEEE xEEEE \ 4data1 2io1 1DiskRowIterI 4ThreadedParserI j y fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS3_17RowBlockContainerIjfEEE_NS_9allocatorISA_EEFbS9_EEE ƢvE_NS_9allocatorIS6_EEFvvEEE Ę\ 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEEE j y fEEEEE iEEEEE xEEEEE ˙\ 4data1 ң2io1 1DiskRowIterI 4ThreadedParserI j y ۨ fE12TryLoadCacheEvEUl ҤiE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS0_17RowBlockContainerIjfEEE_ vE_ \ \ ʛ\ BasicRowIterI LibSVMParserI İ j y fEE إiEE ΫxEE \ fEE iEE ԫxEE \ fEE iEE ګxEE \ fEEEE iEEEE xEEEE ՜\ fEEEE ئiEEEE xEEEE \ fEEEE iEEEE xEEEE \ fE12TryLoadCacheEvEUl ΧiE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS3_17RowBlockContainerIyfEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE ۩\ fEEEEE ըiEEEEE ٬xEEEEE \ fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl ߬xE12TryLoadCacheEvEUl PPNS0_17RowBlockContainerIyfEEE_ թvE_ \ \ \ fEE iEE xEE \ \ ۡ\ \ \ Ѣ\ PPNS3_17RowBlockContainerIjiEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE «\ \ PPNS0_17RowBlockContainerIjiEEE_ vE_ ȫѤ\ \ \ \ ݦ\ \ \ \ \ PPNS3_17RowBlockContainerIyiEEE_NS_9allocatorISA_EEFbS9_EEE ӬvE_NS_9allocatorIS6_EEFvvEEE \ \ PPNS0_17RowBlockContainerIyiEEE_ vE_ \ ª\ \ ޫ\ \ \ \ ٬\ \ PPNS3_17RowBlockContainerIjxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE ĭ\ ˮ\ PPNS0_17RowBlockContainerIjxEEE_ ܮvE_ \ \ ʰ\ \ \ \ ձ\ \ \ PPNS3_17RowBlockContainerIyxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE \ \ PPNS0_17RowBlockContainerIyxEEE_ vE_ \ \ \ \ jfEE ְyfEE \ extParserBaseI hreadedParserI Ա j y fEE iEE xEE ܶ\ j y ٶ fEE αiEE xEE \ jfEE yfEE \ jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE \ jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE \ jfEC1EPNS3_10ParserImplIjfEEEUl ijyfEC1EPNS3_10ParserImplIyfEEEUl PPNS_6vectorINS3_17RowBlockContainerIjfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE \ jfEENS_9allocatorIS6_EEEEEEE yfEENS_9allocatorIS6_EEEEEEE \ jfEC1EPNS0_10ParserImplIjfEEEUl ҵyfEC1EPNS0_10ParserImplIyfEEEUl PPNSt3__16vectorINS0_17RowBlockContainerIjfEENS6_9allocatorIS9_EEEEE_ vE_ \ \ \ \ fEE ӶiEE xEE ս\ fEE iEE xEE ź\ fEE iEE xEE ˺\ \ Ǿ\ \ PPNS_6vectorINS3_17RowBlockContainerIyfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE \ \ PPNSt3__16vectorINS0_17RowBlockContainerIyfEENS6_9allocatorIS9_EEEEE_ vE_ \ \ \ jfEE yfEE \ \ j y Թ fEE ιiEE xEE \ fEE iEE xEE \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ 1 23IndexedRecordIOSplitterE 5 ʻ8ThreadedInputSplitE 6 2LineSplitterE 4InputSplitBaseE 0FileS SingleFileSplitE LocalFileSystemE \ \ \ \ \ 8ThreadedInputSplitC1EPNS3_14InputSplitBaseEmEUl 6CachedInputSplit1 PPNS5_5ChunkEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS7_EEFvvEEE \ \ 8ThreadedInputSplitC1EPNS0_14InputSplitBaseEmEUl 6CachedInputSplit1 PPNS2_5ChunkEE_ vE_ \ \ \ CachedInputSplitE RecordIOSplitterE \ 4InitCachedIterEvEUl ӿ5InitPreprocIterEvEUlPPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE PPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE 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0 m1Parse n2ParseBooleanEv n3kMaxNumLengthE SkipSpacesEv nParseArrayEv n
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Ћ Л Json odata tree 4 oaSERKS0_ p LoadE oDumpES0_PNSt3__11 o NS_10StringViewE oPNS_10JsonReaderE o 3basic_ostreamIcNS1_11char_traitsIcEEEEb p2basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEb p 5StartERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE r4StopERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE r Ђ 21CollectFromOtherRanksEv s15PrintStatisticsERKNSt3__13mapINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEENS2_4pairImmEENS2_4lessIS9_EENS7_INSA_IKS9_SB_EEEEEE s5PrintEv s 3 s5BitORE M tSumE axE tinE ޭ mEEvPKvPviRKN3MPI8DatatypeE vyEEvPKvPviRKN3MPI8DatatypeE фjEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE ƭiEEvPKvPviRKN3MPI8DatatypeE ̭lEEvPKvPviRKN3MPI8DatatypeE ҭdEEvPKvPviRKN3MPI8DatatypeE حк Version vDMatrix zLearner RegTree 4 w6StringERKNSt3__15tupleIJiiiEEE x8kInvalidE LoadE wS w RKNS_4JsonEb wPN4dmlc6StreamE w a welfEv x veEPN xmeERKNSt3__15tupleIJiiiEEE x S_4JsonE x4dmlc6StreamE x 8RegistryIN x1 4data1 6 2io 7xgboost yS_16ParserFactoryRegI 4 y1 9MetricRegEE3GetEv data19SparsePageFormatRegINS1_ ytree17SplitEvaluatorRegEE3GetEv 1 z7CSCPageEEEE3GetEv z 0SparsePageEEEE3GetEv z3SortedCSCPageEEEE3GetEv z1EllpackPageEEEE3GetEv z 6Create |4LoadERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEbbS9_m 15SaveToLocalFileERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE INS_4data1 }EONSt3__110unique_ptrINS_10DataSourceINS_10SparsePageEEENS1_14default_deleteIS5_EEEERKNS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE 2DenseAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 0CS 6DataTableAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 1FileAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 9DMatrixSliceAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm RAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm CAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm В 5ClearEv 10LoadBinaryEPN4dmlc6StreamE 7SetInfoEPKc 9kNumFieldE PKvNS_8DataTypeEm RKNSt3__112basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEE 4PushERKS0_ ń7PushCSCERKS0_ ˄ 7xgboost4data16SparsePageWriterINS7_10SparsePageEEC1ERKNS_6vectorINS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEENSG_ISI_EEEESM_mEUlvE_EEEEEPvSP_ 4dmlc Я 12ThreadedIterIN 4data14TextParserBaseI 7xgboost ˆS 1 7CSCPageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ 0SparsePageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ 3SortedCSCPageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ C D 2E ψ1E v PNS_7DMatrixERKNS_10BatchParamE Ш v PNS_7DMatrixERKNS_10BatchParamE 2Ev ˉ1Ev щ 1 49__dmlc_registry_file_tag_sparse_page_raw_format__Ev 7 Ċ5SimpleCSRSource Î3SimpleDMatrix EllpackPageSource SparsePageDMatrix C 11BeforeFirstEv 4NextEv 5ValueEv 2EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE 1EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE б data1 ܍tree14SplitEvaluator17ComputeSplitScoreEjjRKNS0_9GradStatsES4_ 7 5SimpleCSRSource 3SimpleDMatrix EllpackPageSource5ValueEv SparsePageDMatrix ٕ 5ClearEv 8CopyFromEPNS_7DMatrixE 1 4NextEv з 0LoadBinaryEPN4dmlc6StreamE 1BeforeFirstEv 10SaveBinaryEPN4dmlc6StreamE 5ValueEv C 4InfoEv ޓ1 22GetSortedColumnBatchesEv 2INS0_1 Ԑ1INS0_1 ё 2DenseAdapterEEEPT_fi ˑ0CS Β6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi Ɠ9DMatrixSliceAdapterEEEPT_fi ғ 2DenseAdapterEEEPT_fi Ȓ0CS 6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi ̓9DMatrixSliceAdapterEEEPT_fi ؓ RAdapterEEEPT_fi CAdapterEEEPT_fi RAdapterEEEPT_fi CAdapterEEEPT_fi Ё Ѝ 4InfoEv 14SingleColBlockEv 3Get ה6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE ColDensityEm RowBatchesEv Щ 4InfoEv ӕ1 22GetSortedColumnBatchesEv 4InfoEv 14SingleColBlockEv 3Get ̖6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE RowBatchesEv ColDensityEm gbm ٗobj Ϲ2FeatureInteractionConstraintHost 3 1 28DeprecatedGBLinearModelParam11__MANAGER__Ev 6GBTree 5__dmlc_registry_file_tag_gblinear__Ev 3__dmlc_registry_file_tag_gbtree__Ev 8GBLinearTrainParam11__MANAGER__Ev 3GBLinearModel9LoadModelERKNS_4JsonE ߚ6GBTree 4DartTrainParam11__MANAGER__Ev 1GBTreeModel 1 6GBTree 3GBLinearModel9SaveModelEPNS_4JsonE ٚ1GBTreeModel 8GradientBoosterRegEE3GetEv ޛ6LinearUpdaterRegEE3GetEv 4 2PredictorRegEE3GetEv 0TreeGenRegEE3GetEv ! 9 1 2 7DoBoostEPNS_7DMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_11ObjFunctionE ͣ ConfigureERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE LoadModelERKNS_4JsonE ڥ ! 7ConfigureUpdatersEv 1 3BoostNewTreesEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEiPNSt3__16vectorINSA_10unique_ptrINS_7RegTreeENSA_14default_deleteISD_EEEENSA_9allocatorISG_EEEE ӣ0LoadConfigERKNS_4JsonE ߣ В! InitUpdaterERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE CommitModelEONSt3__16vectorINS3_INS2_10unique_ptrINS_7RegTreeENS2_14default_deleteIS5_EEEENS2_9allocatorIS8_EEEENS9_ISB_EEEE ٣ ! 2ConfigureWithKnownDataERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEEPNS_7DMatrixE 6PerformTreeMethodHeuristicEPNS_7DMatrixE ǣ Ь! ! ! ! ! ! hn S ʰI VN 8_N 16_N7xgboost7LearnerD 7xgboost ܤK7xgboost3gbm6GBTree10SaveConfigEPNS_4JsonE ԥ 3gbm6GBTree10LoadConfigERKNS_4JsonE 7LearnerD " 10SaveConfigEPNS_4JsonE Υ9SaveModelEPNS_4JsonE " " " " ModelParam11__MANAGER__Ev TrainParam11__MANAGER__Ev " " " 4SaveEPN4dmlc6StreamE 9SaveModelEPNS_4JsonE & 4LoadEPN4dmlc6StreamE 9LoadModelERKNS_4JsonE & Х& & Learner19AllowLazyCheckPointEv RegTree & D è6CreateERKNSt3__16vectorINS1_10shared_ptrINS_7DMatrixEEENS1_9allocatorIS5_EEEE 2Ev ڨ1Ev 0Ev & & 1Ev 0Ev & 1Ev 0Ev & & & & ModelParamC ҩTrainParam11__MANAGER__Ev 2ERKNS_23LearnerModelParamLegacyEf 1ERKNS_23LearnerModelParamLegacyEf & & & & 1 ˪6kCpuIdE 1__MANAGER__Ev 4ConfigureGpuIdEb & & & * - LinearUpdater6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE ConsoleLogger Tr ϱGraphvizParam11__MANAGER__Ev - 1 Ь4 6LinearTrainParam11__MANAGER__Ev 5CoordinateParam11__MANAGER__Ev - - 5__dmlc_registry_file_tag_updater_coordinate__Ev 2__dmlc_registry_file_tag_updater_shotgun__Ev - / 6CustomLogMessage3LogERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE 2 0 8TemporaryDirectory15RecursiveDeleteERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE / D 9 1 C 6param_E 2Ev 1Ev ɱ / ShouldLogENS0_12LogVerbosityE ñConfigureERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEE / / ackerLoggerD eeGenerator 2Ev 1Ev / / / / 6DefaultVerbosityEv 5GlobalVerbosityEv 7global_verbosity_E / / 2E 1E NS0_12LogVerbosityE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE / NS0_12LogVerbosityE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE / / / 4 3 2 5__dmlc_registry_file_tag_elementwise_metric__Ev 4__dmlc_registry_file_tag_multiclass_metric__Ev 0 dEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE ɹcEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE 0 1 1 1 8__dmlc_registry_file_tag_rank_metric__Ev ù5__make_MetricReg_PossionNegLoglik__E 2__make_MetricReg_GammaDeviance__E 1__make_MetricReg_ 3__make_MetricReg_TweedieNLogLik__E 2 3 3 41__dmlc_registry_file_tag_ 22 1 9ListEntry7CmpPredERKS1_S3_ ƽ 6__dmlc_registry_file_tag_hinge_obj__Ev 5__dmlc_registry_file_tag_rank_obj__Ev 4 multiclass_obj__Ev regression_obj__Ev ̽ 5 SoftmaxMultiClassParam11__MANAGER__Ev PoissonRegressionParam11__MANAGER__Ev ؽTweedieRegressionParam11__MANAGER__Ev 5 ObjFunctionRegEE3GetEv TreeUpdaterRegEE3GetEv 6 6 6 5LambdaRankParam11__MANAGER__Ev 2RegLossParam11__MANAGER__Ev ҽ 6 7 Ѕ9 9 9 9 = ? 9ConfigureERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEE 6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterENS1_10shared_ptrINS1_13unordered_mapIPNS_7DMatrixENS_20PredictionCacheEntryENS1_4hashISG_EENS1_8equal_toISG_EENS5_INS1_4pairIKSG_SH_EEEEEEEE ? ? 9 5ResetEv ConfigureERKNS_4tree10TrainParamEj SplitImplEijii С? ? е? Ш@ @ 1 4 39__dmlc_registry_file_tag_updater_sync__Ev 4SplitEvaluator 0TrainParam11__MANAGER__Ev 8ColMakerTrainParam11__MANAGER__Ev 7QuantileHistMaker 6CreateERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 4InitEPKNS0_10TrainParamE 5ResetEv 8AddSplitEjjjjff ж@ @ @ @ @ A A ЅA 6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS_10FeatureMapEb 5MatchERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS1_3mapIS7_S7_NS1_4lessIS7_EENS5_INS1_4pairIS8_S7_EEEEEE A КA 9 4SaveEPN4dmlc6StreamE 2 8TreeShapERKNS0_4FVecEPfjjPNS_11PathElementEffiijf DumpModelERKNS_10FeatureMapEbNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE SaveModelEPNS_4JsonE A 4LoadEPN4dmlc6StreamE 9LoadModelERKNS_4JsonE 1 A A A A 8FillNodeMeanValuesEv 7FillNodeMeanValueEi B B 8CalculateContributionsApproxERKNS0_4FVecEPf 2CalculateContributionsERKNS0_4FVecEPfij B B B B B B E I ЙI 3__dmlc_registry_file_tag_updater_colmaker__Ev 4__dmlc_registry_file_tag_updater_histmaker__Ev 0__dmlc_registry_file_tag_updater_prune__Ev 8__dmlc_registry_file_tag_updater_quantile_hist__Ev 2__dmlc_registry_file_tag_updater_ I I 2ReducerSafe_IN7xgboost4tree 3InvokeLambda_EPv 1 9GradStatsEXadL_ZNS3_6ReduceERS3_RKS3_EEEEvPKvPviRKN3MPI8DatatypeE 0SplitEntryEXadL_ZNS3_6ReduceERS3_RKS3_EEEEvPKvPviRKN3MPI8DatatypeE 1SketchMaker7SKStatsEXadL_ZNS4_6ReduceERS4_RKS4_EEEEvPKvPviRKN3MPI8DatatypeE K jEEvPKvPviRKN3MPI8DatatypeE cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE İL L M N N O O 9ConfigureERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE 6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEE 21UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE 7Builder O O P 2 1 6UpdateERKNS_6common16GHistIndexMatrixERKNS3_21GHistIndexBlockMatrixERKNS3_12ColumnMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEPNS_7RegTreeE 8InitDataERKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS7_9allocatorISB_EEEERKNS_7DMatrixERKNS_7RegTreeE 9LossGuideENS2_11ExpandEntryES3_ 1UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE 4BuildHistogramsLossGuideENS2_11ExpandEntryERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSD_9allocatorISH_EEEE 0 6SplitContainsMissingValuesENS0_9GradStatsERKNS1_9NodeEntryE ДP 4 1 3 0ApplySplitEiRKNS_6common16GHistIndexMatrixERKNS3_12ColumnMatrixERKNS3_14HistCollectionERKNS_7DMatrixEPNS_7RegTreeE 9 SyncHistogramsEiiPNS_7RegTreeE BuildNodeStatsERKNS_6common16GHistIndexMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSB_9allocatorISF_EEEE EvaluateSplitsERKNS_6common16GHistIndexMatrixERKNS3_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS2_11ExpandEntryENSG_9allocatorISI_EEEE P P AddHistRowsEPiS3_ InitNewNodeEiRKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS7_9allocatorISB_EEEERKNS_7DMatrixERKNS_7RegTreeE P BuildLocalHistogramsERKNS_6common16GHistIndexMatrixERKNS3_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSC_9allocatorISG_EEEE ApplySplitSparseDataENS_6common16RowSetCollection4ElemERKNS3_16GHistIndexMatrixEPNSt3__16vectorINS4_5SplitENS9_9allocatorISB_EEEERKNS3_6ColumnEjjib P P P P EvaluateSplitERKNSt3__16vectorINS2_11ExpandEntryENS3_9allocatorIS5_EEEERKNS_6common16GHistIndexMatrixERKNSB_14HistCollectionERKNS_7DMatrixERKNS_7RegTreeE SplitSiblingsERKNSt3__16vectorINS2_11ExpandEntryENS3_9allocatorIS5_EEEEPS8_SB_PNS_7RegTreeE P P Q ExpandWith ApplySplitDenseDataENS_6common16RowSetCollection4ElemERKNS3_16GHistIndexMatrixEPNSt3__16vectorINS4_5SplitENS9_9allocatorISB_EEEERKNS3_6ColumnEib DepthWiseERKNS_6common16GHistIndexMatrixERKNS3_21GHistIndexBlockMatrixERKNS3_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSH_9allocatorISL_EEEE LossGuideERKNS_6common16GHistIndexMatrixERKNS3_21GHistIndexBlockMatrixERKNS3_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSH_9allocatorISL_EEEE Q УQ Q Q Q Q Q Q refresh__Ev skmaker__Ev S оT T U 7 6LibFMParserParam11__MANAGER__Ev 4CSVParserParam11__MANAGER__Ev 8CreateLibSVMParserI 5CreateCSVParserI LibSVMParserParam11__MANAGER__Ev CreateLibFMParserI U U U RowBlockIterI ThreadedIterINS_2io14InputSplitBase5ChunkEE14NotImplementedEv j y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ U fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ U U U V V ParserI Stream6CreateEPKcS2_b j y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ V fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ V ЩV V V V j y fEEE3GetEv iEEE3GetEv xEEE3GetEv V V V fEEE3GetEv iEEE3GetEv xEEE3GetEv V V V jfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj yfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj V W jfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj yfEEPNS_6ParserIT_fEERKNSt3__112basic_stringIcNS6_11char_traitsIcEENS6_9allocatorIcEEEERKNS6_3mapISC_SC_NS6_4lessISC_EENSA_INS6_4pairISD_SC_EEEEEEjj W W j y fEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj iEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj xEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj W fEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj iEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj xEEPNS_6ParserIT_T0_EERKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEERKNS7_3mapISD_SD_NS7_4lessISD_EENSB_INS7_4pairISE_SD_EEEEEEjj W W W W W 7_ _6vectorINS7_4data17RowBlockContainerI 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ j y fEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ iEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ xEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ X fEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ iEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ xEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ Y Z [ І] ^ j y փ fE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjfEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ iE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjiEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ xE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjxEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ _ jfEENS_9allocatorISC_EEEEE4InitENS_8functionIFbPPSF_EEENSH_IFvvEEEEUlvE_EEEEEPvSQ_ ЃyfEENS_9allocatorISC_EEEEE4InitENS_8functionIFbPPSF_EEENSH_IFvvEEEEUlvE_EEEEEPvSQ_ ` fE8FillDataEPNS_6vectorINS8_17RowBlockContainerIyfEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ iE8FillDataEPNS_6vectorINS8_17RowBlockContainerIyiEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ 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BatchEPNS_10InputSplit4BlobEm g NextBatchExEPNS0_14InputSplitBase5ChunkEm BeforeFirstEv g g кg 4 1 D 8StripEndENSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEc 9ReadChunkEPvPm ѓ5Chunk ד InitEPNS0_10FileSystemEPKcmb ReadEPvm ˓ g 7InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb 4ResetPartitionEjj 1BeforeFirstEv 3ConvertToURIsERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE œ6ExtractNextChunkEPNS_10InputSplit4BlobEPNS1_5ChunkE g g g 2Ev 1Ev 0Ev g g g g g h h 4LoadEPS1_m 6AppendEPS1_m h h h k k 1 4OpenERKNS0_3URIEPKcb Օ 1 3ListDirectoryERKNS0_3URIEPNSt3__16vectorINS0_8FileInfoENS5_9allocatorIS7_EEEE ϕ GetPathInfoERKNS0_3URIE ɕOpenForReadERKNS0_3URIEb ە k k l l 1 4InitEiPPc 8FinalizeEv 9 3AllreduceBase ޗ5AllreduceRobust 2 1DataRequestERKNSt3__14pairIbiEERKNS1_6vectorIcNS1_9allocatorIcEEEEm 0Allreduce_EPvmmPFvPKvS1_iRKN3MPI8DatatypeEENS0_3mpi8DataTypeENSA_6OpTypeEPFvS1_ES1_PKciSG_ ڨ C 4InitEiPPc 1 ۘ8S 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PPNS0_17RowBlockContainerIjxEEE_ vE_ і} } } } ݘ} } } } } PPNS3_17RowBlockContainerIyxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE } } PPNS0_17RowBlockContainerIyxEEE_ vE_ } } } ޝ} jfEE yfEE } extParserBaseI hreadedParserI j ğy fEE ۟iEE xEE ݨ} j y fEE iEE xEE } jfEE yfEE ɥڞ} jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE ϥ} jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE ե؟} jfEC1EPNS3_10ParserImplIjfEEEUl yfEC1EPNS3_10ParserImplIyfEEEUl ۥ PPNS_6vectorINS3_17RowBlockContainerIjfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE } jfEENS_9allocatorIS6_EEEEEEE yfEENS_9allocatorIS6_EEEEEEE ٦ڡ} jfEC1EPNS0_10ParserImplIjfEEEUl yfEC1EPNS0_10ParserImplIyfEEEUl ߦ PPNSt3__16vectorINS0_17RowBlockContainerIjfEENS6_9allocatorIS9_EEEEE_ ڤvE_ } £} } } fEE iEE ŨxEE } fEE iEE ˨xEE } fEE åiEE ѨxEE ӥ} } } } PPNS_6vectorINS3_17RowBlockContainerIyfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE ӦvE_NS_9allocatorIS9_EEFvvEEE } } PPNSt3__16vectorINS0_17RowBlockContainerIyfEENS6_9allocatorIS9_EEEEE_ vE_ ̩} Ϊ} «} jfEE էyfEE ۧ} } j y fEE iEE xEE ר} fEE iEE xEE ٬} } } } ͭ} } } } } ̮} } } } } ӯ} } } 1 23IndexedRecordIOSplitterE 5 8ThreadedInputSplitE 6 2LineSplitterE 4InputSplitBaseE 0FileS SingleFileSplitE LocalFileSystemE а} } } } Ա} 8ThreadedInputSplitC1EPNS3_14InputSplitBaseEmEUl 6CachedInputSplit1 PPNS5_5ChunkEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS7_EEFvvEEE ެ} } 8ThreadedInputSplitC1EPNS0_14InputSplitBaseEmEUl 6CachedInputSplit1 PPNS2_5ChunkEE_ جvE_ ȳ} } } CachedInputSplitE RecordIOSplitterE ŵ} 4InitCachedIterEvEUl 5InitPreprocIterEvEUlPPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE PPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE vE_NS_9allocatorIS5_EEFvvEEE } 4InitCachedIterEvEUl 5InitPreprocIterEvEUlPPNS0_14InputSplitBase5ChunkEE_ PPNS0_14InputSplitBase5ChunkEE_ vE_ } } } ظ} } } } } } } } } end_stateIcEE lookaheadIcNS_12regex_traitsIcEEEE alternateIcEE match_anyIcEE } nodeIcEE 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3SortedCSCPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE 1EllpackPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE 0Json 1Json ObjectE StringE NumberE ReaderE WriterE JsonArrayE PredictorE ValueE ModelE StringE ObjectE NumberE ReaderE WriterE JsonArrayE predictor12CPUPredictorE PredictorE IntegerE BooleanE Json LearnerImplE ObjFunctionE ɄTreeUpdaterE IntegerE BooleanE ȃ IntegerENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE BooleanENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 脃 basic_stringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE __ ¿ ؊ DMatrixE LearnerE RegTreeE Ў DMatrixE LearnerE RegTreeE 6FieldAccessEntryE 4FieldEntryBaseINS0_10FieldEntryI 7FieldEntryNumericINS0_10FieldEntryI 0FieldEntryI iEEiEE NSt3__1 fEEfEE mEEmEE bEEbEE jEEjEE dEEdEE Ȑ iEEiEE fEEfEE mEEmEE jEEjEE dEEdEE iEE N fEE mEE bEE jEE dEE 葃 bad_function_callE __ SourceINS_ FormatINS_ 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE ThreadedIterIN S RowBlockIterI 7xgboost S ߗ 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE copedThreadE erializableE function6__ l_anchorIcEE r_anchorIcEE back_refIcEE baseIF funcI b vvEEE PN7xgboost PPN N7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES6_EEE 7xgboost 4dmlc S_6vectorIN4dmlc4data17RowBlockContainerI 1 7CSCPageEEEE 0SparsePageEEEE 3SortedCSCPageEEEE ZN PF 7xgboost4 4dmlc data16SparsePageSourceINS2_ tree1 č 1 7CSCPageEEC1ERKNS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEESE_EUl 0SparsePageEEC1ERKNS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEESE_EUl 3SortedCSCPageEEC1ERKNS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEESE_EUl PPS5_E_NSA_ISH_EEFbSG_EEE vE_NSA_ISF_EEFvvEEE 7xgboost4 4dmlc data16SparsePageSourceINS_ tree1 1 7CSCPageEEC1ERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEESC_EUl 0SparsePageEEC1ERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEESC_EUl 3SortedCSCPageEEC1ERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEESC_EUl PPS2_E_ vE_ data1 tree1 7 5SimpleCSRSourceE 3SimpleDMatrixE EllpackPageSourceE SparsePageDMatrixE EllpackPageSourceE SparsePageDMatrixE ؘ BatchIteratorImplINS_ GraphvizGeneratorE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1EllpackPageEEE 蚃 impleBatchIteratorImplINS_ parseBatchIteratorImplINS0_1 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1EllpackPageEEE Л Ȝ О 螃 П 6SparsePageSourceINS_ 7EllpackPageSourceENS_11EllpackPageEEE 1 7CSCPageEEES3_EE 0SparsePageEEES3_EE 3SortedCSCPageEEES3_EE PPS5_E_NSA_ISH_EEFbSG_EEE vE_NSA_ISF_EEFvvEEE PPS2_E_ vE_ ृ PPS5_E_NSA_ISH_EEFbSG_EEE vE_NSA_ISF_EEFvvEEE PPS2_E_ vE_ Ъ 4 1 6MetricEPKcEEE 9PredictorEPKNS2_16GenericParameterENS_10shared_ptrINS_13unordered_mapIPNS2_7DMatrixENS2_20PredictionCacheEntryENS_4hashISB_EENS_8equal_toISB_EENS_9allocatorINS_4pairIKSB_SC_EEEEEEEEEEE و data16SparsePageFormatINS2_ tree14SplitEvaluatorENS_10unique_ptrIS4_NS_14default_deleteIS4_EEEEEEE ي 1 7CSCPageEEEvEEE 0SparsePageEEEvEEE 3SortedCSCPageEEEvEEE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 12basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEEEES9_EE 6vectorIiNS3_9allocatorIiEEEEEES7_EE St3__1 7xgboost1 12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEEE 6vectorIiNS2_9allocatorIiEEEEEE ȳ д 贃 5GradientBoosterERKNS_6vectorINS_10shared_ptrINS2_7DMatrixEEENS_9allocatorIS8_EEEEPKNS2_17LearnerModelParamEEEE 3 1 跃 gbm obj Є 8GBLinearE 1 6GBTreeE 4DartE 1 6GBTreeE 3GBLinearModelE 1GBTreeModelE 踃 3GBLinearModelE 1GBTreeModelE 5TreeProcessTypeEEE 3 0TreeMethodEEE PredictorTypeEEE DataSplitModeEEE S_13unordered_mapIPN7xgboost7DMatrixENS2_20PredictionCacheEntryENS_4hashIS4_EENS_8equal_toIS4_EENS_9allocatorINS_4pairIKS4_S5_EEEEEENSA_ISF_EEEE 7xgboost16HostDeviceVectorIjEENS_9allocatorIS3_EEEE Ã ă ă ă ƃ ƃ Ƀ ʃ ˃ ˃ ̃ LinearUpdaterEvEEE TreeGeneratorERKNS2_10FeatureMapENS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEEbEEE ̓ LinearUpdaterE T ƋJsonGeneratorE 1 2 7CoordinateUpdaterE 5FeatureSelectorE 4ShotgunUpdaterE 1 2 CyclicFeatureSelectorE GreedyFeatureSelectorE RandomFeatureSelectorE ShuffleFeatureSelectorE ThriftyFeatureSelectorE σ Ѓ Ѓ у ҃ Ӄ ԃ 1 7Eval 9EvalAucPRE 8EvalNDCGE 3Eval 4EvalM ʂ6EvalMultiLogLossE 2EvalRankListE EWiseBaseINS0_ PrecisionE 1 20EvalPoissonNegLogLikEEE 9EvalErrorEEE 1EvalRowRMSEEEE 2EvalRowRMSLEEEE 0EvalRowMAEEEE 4EvalRowLogLossEEE 7EvalGammaDevianceEEE 6EvalGammaNLogLikEEE 8EvalTweedieNLogLikEEE Âԃ փ ׃ ك ۃ ܃ ރ ClassBaseINS0_1 atchErrorE 4EvalMatchErrorEEE 6EvalMultiLogLossEEE A ЃMAPE CoxE MSE ucE ObjFunctionEvEEE TreeUpdaterEvEEE 8HingeObjE 20SoftmaxMultiClassObjE 1 3 Å0RegLossObjINS0_ 7 5GammaRegressionE ˈ LambdaRankObjINS0_2 CoxRegressionE Ĉ 8PairwiseLambdaWeightComputerEEE ӆ4NDCGLambdaWeightComputerEEE چ3MAPLambdaWeightComputerEEE 1 22LogisticClassificationEEE 6LinearSquareLossEEE 5SquaredLogErrorEEE 8LogisticRegressionEEE 1LogisticRawEEE PoissonRegressionE TweedieRegressionE ҈ 4SplitEvaluatorE 7QuantileHistMaker 1 ߉8ColMaker 9 ߌ23GlobalProposalHistMakerE 4SplitEvaluatorE Ҋ0 9MonotonicConstraintE 2DistColMaker 1 7QuantileHistMaker 3TreeRefresherE ޕ ؓ ElasticNetE TreePrunerE ؖ ؚ ț reeGeneratorE extGeneratorE 蜄 П С Т ȣ E 7BuilderE ࣄ E ь7BuilderE ،ئ BaseMakerE HistMakerE Щ CQHistMakerE SketchMakerE TreeSyncherE 詄 1CQHistMaker10CreateHistERKNS_6vectorINS2_6detail20GradientPairInternalIfEENS_9allocatorIS8_EEEEPNS2_7DMatrixERKNS5_IjNS9_IjEEEERKNS2_7RegTreeEEUlvE_NS9_ISN_EEFvvEEE 3TreeRefresher6UpdateEPNS2_16HostDeviceVectorINS2_6detail20GradientPairInternalIfEEEEPNS2_7DMatrixERKNS_6vectorIPNS2_7RegTreeENS_9allocatorISF_EEEEEUlvE_NSG_ISL_EEFvvEEE 1CQHistMaker10CreateHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS2_9allocatorIS6_EEEEPNS_7DMatrixERKNS3_IjNS7_IjEEEERKNS_7RegTreeEEUlvE_ ޒ3TreeRefresher6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEEEUlvE_ Ȭ خ E 7BuilderE 谄 E 7BuilderE б 豄 в bN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES6_ENS_9allocatorIS8_EES7_EE vvENS_9allocatorIS3_EES2_EE ಄ bN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_E vvE bN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_E וvvE 趄 ط ع j y fEE iEE ͢xEE 1 9CSVParserI 1 2 ǝ0ParserImplI 4T ܩ DiskRowIterI LibFMParserI j y מ fEE iEE ԢxEE j y fEEEE ؗiEEEE ۢxEEEE _ t3__16vectorINS_4data17RowBlockContainerI 4data17RowBlockContainerI Ҙ2io14InputSplitBase5ChunkEEE j ޘy fEEEE iEEEE xEEEE 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEEE j Ιy fEEEEE iEEEEE xEEEEE 4data1 2io1 1DiskRowIterI 4ThreadedParserI j y fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS3_17RowBlockContainerIjfEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE 4data1 2io1 ڶ 1DiskRowIterI 4ThreadedParserI j y fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl أxE12TryLoadCacheEvEUl PPNS0_17RowBlockContainerIjfEEE_ vE_ BasicRowIterI LibSVMParserI j y fEE iEE xEE Ч fEEEE iEEEE xEEEE ק fEE ОiEE xEE ާ fEE iEE xEE fEEEE iEEEE xEEEE fEEEE iEEEE xEEEE fEEEEE ݟiEEEEE ĤxEEEEE fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl ˤxE12TryLoadCacheEvEUl PPNS3_17RowBlockContainerIyfEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS0_17RowBlockContainerIyfEEE_ vE_ Ä Ä Ą fEE iEE xEE Ą ń ń ń Ƅ Ƅ DŽ PPNS3_17RowBlockContainerIjiEEE_NS_9allocatorISA_EEFbS9_EEE ѣvE_NS_9allocatorIS6_EEFvvEEE DŽ PPNS0_17RowBlockContainerIjiEEE_ vE_ DŽ Ȅ Ȅ Ʉ Ʉ ʄ ʄ ʄ ʄ ˄ PPNS3_17RowBlockContainerIyiEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE ˄ PPNS0_17RowBlockContainerIyiEEE_ vE_ ̄ ̄ ̈́ ̈́ ΄ ΄ ΄ τ τ Є PPNS3_17RowBlockContainerIjxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE §Є PPNS0_17RowBlockContainerIjxEEE_ vE_ ɧЄ ф ф ҄ ӄ ӄ ӄ ӄ Ԅ Ԅ PPNS3_17RowBlockContainerIyxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE Մ PPNS0_17RowBlockContainerIyxEEE_ vE_ Մ ք ք ք j y ͯ fEE թiEE xEE ׄ extParserBaseI hreadedParserI Ū j y fEE iEE xEE ׄ jfEE yfEE jfEE תyfEE ڄ jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE ڄ jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE ڄ jfEENS_9allocatorIS6_EEEEEEE yfEENS_9allocatorIS6_EEEEEEE ۄ jfEC1EPNS3_10ParserImplIjfEEEUl yfEC1EPNS3_10ParserImplIyfEEEUl PPNS_6vectorINS3_17RowBlockContainerIjfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE ۄ jfEC1EPNS0_10ParserImplIjfEEEUl ȮyfEC1EPNS0_10ParserImplIyfEEEUl PPNSt3__16vectorINS0_17RowBlockContainerIjfEENS6_9allocatorIS9_EEEEE_ vE_ ۄ ܄ ܄ fEE ƯiEE xEE γ݄ fEE iEE xEE ճ݄ fEE iEE xEE ܳބ ބ PPNS_6vectorINS3_17RowBlockContainerIyfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE PPNSt3__16vectorINS0_17RowBlockContainerIyfEENS6_9allocatorIS9_EEEEE_ vE_ jfEE yfEE j y ܲ fEE ղiEE xEE dz fEE iEE xEE 1 23IndexedRecordIOSplitterE 5 8ThreadedInputSplitE 6 2LineSplitterE 4InputSplitBaseE ͼ0FileS SingleFileSplitE LocalFileSystemE 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18EvalTweedieNLogLik4NameEvE4name TextGenerator JsonGenerator 9 7IntegerERKNS_7RegTreeEijE16kIntegerTemplate 10QuantitiveERKNS_7RegTreeEijE19kQuantitiveTemplate 8 IndicatorERKNS_7RegTreeEijE18kIndicatorTemplate PlainNodeERKNS_7RegTreeEijE13kNodeTemplate BuildTreeERKNS_7RegTreeE 3 7GraphvizGenerator TextGenerator JsonGenerator 9 7IntegerERKNS_7RegTreeEijE16kIntegerTemplate 10QuantitiveERKNS_7RegTreeEijE19kQuantitiveTemplate 8 IndicatorERKNS_7RegTreeEijE18kIndicatorTemplate PlainNodeERKNS_7RegTreeEijE13kNodeTemplate BuildTreeERKNS_7RegTreeE Ƚ NodeStatERKNS_7RegTreeEiE13kStatTemplate LeafNodeERKNS_7RegTreeEijE13k н NodeStatERKNS_7RegTreeEiE13kStatTemplate LeafNodeERKNS_7RegTreeEijE13k 轅 LeafTemplate StatTemplate LeafTemplate StatTemplate Ⱦ ijE13kNodeTemplate E13kTreeTemplate о ijE13kNodeTemplate E13kTreeTemplate 辅 9 7IntegerERKNS_7RegTreeEijE16kIntegerTemplate 10QuantitiveERKNS_7RegTreeEijE19kQuantitiveTemplate 8 IndicatorERKNS_7RegTreeEijE18kIndicatorTemplate 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__ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS_6vectorINS2_4data17RowBlockContainerIjfEENS_9allocatorIS7_EEEEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.1 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS_6vectorINS2_4data17RowBlockContainerIjfEENS_9allocatorIS7_EEEEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 __ZNSt3__114__thread_proxyINS_5tupleIJNS_10unique_ptrINS_15__thread_structENS_14default_deleteIS3_EEEEZN4dmlc12ThreadedIterINS_6vectorINS7_4data17RowBlockContainerIjfEENS_9allocatorISC_EEEEE4InitENS_8functionIFbPPSF_EEENSH_IFvvEEEEUlvE_EEEEEPvSQ_.cold.1 __ZN4dmlc4data14TextParserBaseIyfED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIyfE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyfEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIyfE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyfEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14ThreadedParserIyfEC2EPNS0_10ParserImplIyfEE.cold.1 __ZN4dmlc4data14ThreadedParserIyfEC2EPNS0_10ParserImplIyfEE.cold.2 __ZN4dmlc4data14ThreadedParserIyfEC2EPNS0_10ParserImplIyfEE.cold.3 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS_6vectorINS2_4data17RowBlockContainerIyfEENS_9allocatorIS7_EEEEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.1 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS_6vectorINS2_4data17RowBlockContainerIyfEENS_9allocatorIS7_EEEEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 __ZNSt3__114__thread_proxyINS_5tupleIJNS_10unique_ptrINS_15__thread_structENS_14default_deleteIS3_EEEEZN4dmlc12ThreadedIterINS_6vectorINS7_4data17RowBlockContainerIyfEENS_9allocatorISC_EEEEE4InitENS_8functionIFbPPSF_EEENSH_IFvvEEEEUlvE_EEEEEPvSQ_.cold.1 __ZN4dmlc4data14TextParserBaseIjiED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIjiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjiEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIjiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjiEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIyiED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIyiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyiEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIyiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyiEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIjxED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIjxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjxEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIjxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjxEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIyxED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIyxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyxEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIyxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyxEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc6Stream6CreateEPKcS2_b.cold.1 __ZN4dmlc10SeekStream13CreateForReadEPKcb.cold.1 __ZN4dmlc2io18ThreadedInputSplitC2EPNS0_14InputSplitBaseEm.cold.1 __ZN4dmlc2io18ThreadedInputSplitC2EPNS0_14InputSplitBaseEm.cold.2 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.1 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 __ZNSt3__114__thread_proxyINS_5tupleIJNS_10unique_ptrINS_15__thread_structENS_14default_deleteIS3_EEEEZN4dmlc12ThreadedIterINS7_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_.cold.1 __ZN4dmlc2io16CachedInputSplit14InitCachedIterEv.cold.1 __ZN4dmlc2io16CachedInputSplit14InitCachedIterEv.cold.2 __ZN4dmlc2io16CachedInputSplit15InitPreprocIterEv.cold.1 __ZN4dmlc2io16CachedInputSplit15InitPreprocIterEv.cold.2 __ZN4dmlc2io23IndexedRecordIOSplitter13ReadIndexFileEPNS0_10FileSystemERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE.cold.1 __ZN4dmlc2io14InputSplitBase17InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb.cold.1 __ZN4dmlc2io14InputSplitBase17InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb.cold.2 __ZN4dmlc2io14InputSplitBase13ConvertToURIsERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE.cold.1 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE21__start_matching_listEb.cold.1 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE21__start_matching_listEb.cold.2 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE11__push_loopEmmPNS_16__owns_one_stateIcEEmmb.cold.1 __ZN4dmlc18TemporaryDirectory9IsSymlinkERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE.cold.1 GCC_except_table0 GCC_except_table4 GCC_except_table5 GCC_except_table7 GCC_except_table8 GCC_except_table9 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__ZN7xgboost3obj10RegLossObjINS0_11LogisticRawEE10LoadConfigERKNS_4JsonE __ZNK7xgboost3obj10RegLossObjINS0_11LogisticRawEE10SaveConfigEPNS_4JsonE __ZN7xgboost3obj10RegLossObjINS0_11LogisticRawEE11GetGradientERKNS_16HostDeviceVectorIfEERKNS_8MetaInfoEiPNS4_INS_6detail20GradientPairInternalIfEEEE __ZNK7xgboost3obj10RegLossObjINS0_11LogisticRawEE17DefaultEvalMetricEv __ZN7xgboost3obj10RegLossObjINS0_11LogisticRawEE13PredTransformEPNS_16HostDeviceVectorIfEE __ZNK7xgboost6common9TransformILb0EE9EvaluatorIZNS_3obj10RegLossObjINS4_11LogisticRawEE11GetGradientERKNS_16HostDeviceVectorIfEERKNS_8MetaInfoEiPNS8_INS_6detail20GradientPairInternalIfEEEEEUlmNS0_4SpanIiLm18446744073709551615EEENSK_ISH_Lm18446744073709551615EEENSK_IKfLm18446744073709551615EEESO_SO_E_E9LaunchCPUIJNS8_IiEESI_SA_SA_SA_EEEvSP_DpPT_ _.omp_outlined..123 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__ZN4dmlc2io18ThreadedInputSplitC2EPNS0_14InputSplitBaseEm.cold.2 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.1 __ZNSt3__16threadC2IRZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPS6_EEENS8_IFvvEEEEUlvE_JEvEEOT_DpOT0_.cold.2 __ZNSt3__114__thread_proxyINS_5tupleIJNS_10unique_ptrINS_15__thread_structENS_14default_deleteIS3_EEEEZN4dmlc12ThreadedIterINS7_2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_.cold.1 __ZN4dmlc12ThreadedIterINS_2io14InputSplitBase5ChunkEED2Ev.cold.1 __ZN4dmlc2io16CachedInputSplit14InitCachedIterEv.cold.1 __ZN4dmlc2io16CachedInputSplit14InitCachedIterEv.cold.2 __ZN4dmlc2io16CachedInputSplit15InitPreprocIterEv.cold.1 __ZN4dmlc2io16CachedInputSplit15InitPreprocIterEv.cold.2 __ZN4dmlc2io23IndexedRecordIOSplitter13ReadIndexFileEPNS0_10FileSystemERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE.cold.1 __ZN4dmlc2io14InputSplitBase17InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb.cold.1 __ZN4dmlc2io14InputSplitBase17InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb.cold.2 __ZN4dmlc2io14InputSplitBase13ConvertToURIsERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE.cold.1 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE21__start_matching_listEb.cold.1 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE21__start_matching_listEb.cold.2 __ZNSt3__111basic_regexIcNS_12regex_traitsIcEEE11__push_loopEmmPNS_16__owns_one_stateIcEEmmb.cold.1 __ZN4dmlc18TemporaryDirectory9IsSymlinkERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE.cold.1 GCC_except_table0 GCC_except_table5 GCC_except_table6 GCC_except_table9 GCC_except_table10 GCC_except_table11 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