vendor/libxgboost.dylib in xgb-0.4.0 vs vendor/libxgboost.dylib in xgb-0.4.1
- old
+ new
@@ -1,1014 +1,1079 @@
- @ x __TEXT ! ! __text __TEXT ' ' __stubs __TEXT ) ) __stub_helper __TEXT x1 x1 __gcc_except_tab__TEXT $; H $; __const __TEXT p { p __cstring __TEXT I n I __unwind_info __TEXT \-! r \-! __DATA ! ! __nl_symbol_ptr __DATA ! ! H __got __DATA ! ! I __la_symbol_ptr __DATA ر! @
- ر! __mod_init_func __DATA ! ( ! __const __DATA @! @! __thread_vars __DATA Z" Z" __data __DATA [" [" __thread_ptrs __DATA d" H d" __thread_bss __DATA e" 8
- __bss __DATA Xo" @ __common __DATA " H __LINKEDIT "
p"
0 @rpath/libxgboost.dylib " 0 p" x xw" " & @# # H# ; .% w$ X' ȧ P H .# I v' ,:.P8.:$
-
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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 binary saving only supported by SimpleDMatrix XGDMatrixSetGroup is deprecated, use `XGDMatrixSetUIntInfo` instead. group label weight base_margin label_lower_bound label_upper_bound Unknown float field name group_ptr Unknown uint field name cache_id == 0 Cache ID is not supported yet Check failed: p_predt json str.size() > 2 str[0] == '{' r w text /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/c_api/../data/adapter.h Check failed: at_first_ Cannot reset IteratorAdapter Check failed: columns_ == data::kAdapterUnknownSize || columns_ == batch.columns Number of columns between batches changed from to allocator<T>::allocate(size_t n) 'n' exceeds maximum supported size /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/c_api/../common/common.h XGBoost version not compiled with GPU support. [ ] : %02d:%02d:%02d
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/Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/c_api.cc DMatrix/Booster has not been intialized or has already been disposed. Check failed: p_m : Check failed: m Current DMatrix type does not support set data. Check failed: static_cast<std::shared_ptr<DMatrix>*>(handle) ->get() ->Info() .group_ptr_.size() == 0U slice does not support group structure binary saving only supported by SimpleDMatrix XGDMatrixSetGroup is deprecated, use `XGDMatrixSetUIntInfo` instead. group cache_id == 0 Cache ID is not supported yet Check failed: p_predt json str.size() > 2 str[0] == '{' r w text /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/adapter.h Check failed: at_first_ Cannot reset IteratorAdapter Check failed: columns_ == data::kAdapterUnknownSize || columns_ == batch.columns Number of columns between batches changed from to allocator<T>::allocate(size_t n) 'n' exceeds maximum supported size /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../common/common.h XGBoost version not compiled with GPU support. /Users/runner/work/ml-builds/ml-builds/xgboost/src/c_api/../data/proxy_dmatrix.h Slicing DMatrix is not supported for Proxy DMatrix. Not implemented. [ ] : %02d:%02d:%02d
Stack trace:
[bt] ( ) _Z DMLC_LOG_STACK_TRACE_DEPTH %zu 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/2.262.1/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 [xgboost] Condition %s failed.
- _ptr || _count == 0 /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/common/hist_util.cc batch_size < offset_vec.size() ;unknown;unknown;0;0;; ibegin + inst.size() == iend HistogramCuts 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 SingleThreadBuild: Concat nthread == omp_get_num_threads() N/A summary_array.size() == in_sketchs->size() p_cuts_->cut_values_.HostVector().size() <= std::numeric_limits<uint32_t>::max() cut_size > p_cuts_->cut_ptrs_.HostVector().back() cut.Values().size() > 0U curent_bin_size == kUint32BinsTypeSize sibling.size() == size parent.size() == size /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/common/hist_util.h SparseCuts DenseCuts Row does not lie in any group! bins_type_size == kUint32BinsTypeSize /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/common/column_matrix.h sizeof(BinIdxType) == bins_type_size_ index_ != span_->size() index_ < span_->size() /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/common/./quantile.h invalid init parameter Check failed: nlevel <= std::max(static_cast<size_t>(1), static_cast<size_t>(limit_size * eps)) mingap= , maxgap= , wgap= Check failed: size <= sa.size + sb.size bug in combine /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/include/xgboost/data.h Check failed: impl_ != nullptr fi.Read(&this->size, sizeof(this->size)) == sizeof(this->size) fi.Read(this->data, this->size * sizeof(Entry)) == this->size * sizeof(Entry) Check failed: false /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/common/host_device_vector.cc Size() == other.Size() Size() == other.size() /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/common/io.cc pointer_ <= buffer_.size() Check failed: out Opening failed: /Users/runner/runners/2.262.1/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/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/include/xgboost/json.h beg <= size_ Expecting: " ", got: " " C Invalid cast, from /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/common/probability_distribution.cc Unknown distribution /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/common/survival_util.cc Unknown distribution type Unknown censoring type aft_loss_distribution normal extreme Choice of distribution for the noise term in Accelerated Failure Time model aft_loss_distribution_scale Scaling factor used to scale the distribution in Accelerated Failure Time model Invalid Parameter format for expect but value=' optional, default= , required Invalid Input: ' ', valid values are: ' Required parameter of is not presented value for Parameter exceed bound [ should be greater equal to should be smaller equal to optional, default= /Users/runner/runners/2.262.1/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 key has already been registered in Enum ( exisit! )
- Enums: ), 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/2.262.1/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h *p == ')' Invalid NAN literal statistic count elapsed /Users/runner/runners/2.262.1/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/2.262.1/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 labels_lower_bound labels_upper_bound /Users/runner/runners/2.262.1/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. this->base_margin_.Size() % this->num_row_ == 0 Incorrect size of base margin vector. Unknown data type Unknown key for MetaInfo: group_ptr_.size() == weights_.Size() + 1 Size of weights must equal to number of groups when ranking group is used. group_ptr_.back() == num_row_ Invalid group structure. Number of rows obtained from groups doesn't equal to actual number of rows given by data. weights_.Size() == num_row_ Size of weights must equal to number of rows. labels_.Size() == num_row_ Size of labels must equal to number of rows. labels_lower_bound_.Size() == num_row_ Size of label_lower_bound must equal to number of rows. labels_upper_bound_.Size() == num_row_ Size of label_upper_bound must equal to number of rows. num_nonzero_ <= num_col_ * num_row_ base_margin_.Size() % num_row_ == 0 Size of base margin must be a multiple of number of rows. 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 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() Check failed: v.DeviceIdx() == GenericParameter::kCpuId || device == GenericParameter::kCpuId || v.DeviceIdx() == device Data is resided on a different device than `gpu_id`. Device that data is on: `gpu_id` for XGBoost: /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/data/../common/common.h MetaInfo: Invalid format. Check failed: strm->Read(&name) name == expected_name Expected field: , got: Check failed: strm->Read(&type_val) 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) /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.h Couldn't remove external memory cache file ; you may want to remove it manually .row.page Writing in MB/s, written Check failed: qids.empty() || qids.size() == info.num_row_ SparsePageSource Finished writing to cache_shards.size() != 0U raw Cache file exists already; Is there another DMatrix with the same cache prefix? Otherwise please remove it manually. /Users/runner/runners/2.262.1/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 info.name_shards.size() != 0U 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/2.262.1/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 Check failed: mutex_.try_lock() Multiple threads attempting to use prefetcher float32 float64 bool8 int32 int8 int16 int64 /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/data/../data/adapter.h Unknown data table type. /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page.cc Internal Error: XGBoost is not compiled with CUDA but EllpackPage is required .ellpack.page /Users/runner/runners/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.cc Check failed: param != BatchParam{} Batch parameter is not initialized. param.gpu_id >= 0 param.max_bin >= 2 Check failed: in_stream->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic) invalid input file format /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.h Check failed: page_ != nullptr /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.cc /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.h Check failed: source_ != nullptr .col.page Writing to CSCPageSource: Finished writing to .sorted.col.page SortedCSCPageSource: Finished writing to /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_dmatrix.h Slicing DMatrix is not supported for external memory. Raw binary data format. /Users/runner/runners/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.h /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear.cc get<String>(in["name"]) == "gblinear" model gpu_coord_descent __ Cannot find argument ' ', Possible Arguments:
+ read can not have position excceed buffer length /Users/runner/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 [xgboost] Condition %s failed.
+ _ptr || _count == 0 NaN 0E0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/hist_util.cc batch_size < offset_vec.size() ;unknown;unknown;0;0;; ibegin + inst.size() == iend sibling.size() == size parent.size() == size HistogramCuts 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 local_ptrs.size() >= 1 Build nthreads > 0 page.Size() <= dmat->Info().num_col_ Load balance SingleThreadBuild: Concat nthread == omp_get_num_threads() N/A summary_array.size() == in_sketchs->size() p_cuts_->cut_values_.HostVector().size() <= std::numeric_limits<uint32_t>::max() cut_size > p_cuts_->cut_ptrs_.HostVector().back() cut.Values().size() > 0U curent_bin_size == kUint32BinsTypeSize /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/hist_util.h SparseCuts DenseCuts base_rowid < group_ptr.back() Row: is not found in any group. bins_type_size == kUint32BinsTypeSize /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/column_matrix.h sizeof(BinIdxType) == bins_type_size_ index_ != span_->size() index_ < span_->size() /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/./quantile.h invalid init parameter Check failed: nlevel <= std::max(static_cast<size_t>(1), static_cast<size_t>(limit_size * eps)) mingap= , maxgap= , wgap= Check failed: size <= sa.size + sb.size bug in combine /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/data.h Check failed: impl_ != nullptr fi.Read(&this->size, sizeof(this->size)) == sizeof(this->size) fi.Read(this->data, this->size * sizeof(Entry)) == this->size * sizeof(Entry) Check failed: false /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/host_device_vector.cc Size() == other.Size() Size() == other.size() /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/io.cc pointer_ <= buffer_.size() Check failed: out file:// :// Opening failed: /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/io.h Not implemented rb /Users/runner/work/ml-builds/ml-builds/xgboost/src/common/json.cc Check failed: ret.ec == std::errc() \ \\ \" \b \f \n \r \t \u%04x String Number Object Array Boolean Integer 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 position: , " " \0
" Unknown escape null Expecting null value "null" ch != -1 cursor_.Pos(): , raw_str_.size(): Expecting digit /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/json.h beg <= size_ Expecting: " ", got: " EOF" \0" Invalid cast, from aft_loss_distribution normal extreme Choice of distribution for the noise term in Accelerated Failure Time model aft_loss_distribution_scale Scaling factor used to scale the distribution in Accelerated Failure Time model Invalid Parameter format for expect but value=' optional, default= , required Invalid Input: ' ', valid values are: ' Required parameter of is not presented value for Parameter exceed bound [ should be greater equal to should be smaller equal to optional, default= /Users/runner/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 key has already been registered in Enum ( exisit! )
+ Enums: ), 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/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h *p == ')' Invalid NAN literal statistic count elapsed /Users/runner/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/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) . /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/data.cc key >= builder_base_row_offset num_row num_col num_nonzero labels group_ptr weights base_margin labels_lower_bound labels_upper_bound feature_names feature_types field_cnt == kNumField Wrong number of fields All feature_types must be {int, float, i, q} 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 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. this->base_margin_.Size() % this->num_row_ == 0 Incorrect size of base margin vector. label Unknown data type weight label_lower_bound label_upper_bound Unknown key for MetaInfo: Unknown float field name: Unknown uint32 field name: Unknown data type for getting meta info. size == this->num_col_ Length of must be equal to number of columns. feature_type feature_name Unknown feature info name: Unknown feature info: this->num_col_ == that.num_col_ Number of columns must be consistent across batches. that.group_ptr_.size() != 0 group_ptr_.size() == weights_.Size() + 1 Size of weights must equal to number of groups when ranking group is used. group_ptr_.back() == num_row_ Invalid group structure. Number of rows obtained from groups doesn't equal to actual number of rows given by data. weights_.Size() == num_row_ Size of weights must equal to number of rows. labels_.Size() == num_row_ Size of labels must equal to number of rows. labels_lower_bound_.Size() == num_row_ Size of label_lower_bound must equal to number of rows. labels_upper_bound_.Size() == num_row_ Size of label_upper_bound must equal to number of rows. num_nonzero_ <= num_col_ * num_row_ base_margin_.Size() % num_row_ == 0 Size of base margin must be a multiple of number of rows. 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 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() /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/../common/common.h float32 float64 bool8 int32 int8 int16 int64 /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/../data/adapter.h Unknown data table type. Check failed: v.DeviceIdx() == GenericParameter::kCpuId || device == GenericParameter::kCpuId || v.DeviceIdx() == device Data is resided on a different device than `gpu_id`. Device that data is on: `gpu_id` for XGBoost: MetaInfo: Invalid format. Check failed: strm->Read(&name) name == expected_name Expected field: , got: Check failed: strm->Read(&type_val) 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) /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_source.h Couldn't remove external memory cache file ; you may want to remove it manually .row.page Writing in MB/s, written Check failed: qids.empty() || qids.size() == info.num_row_ SparsePageSource Finished writing to cache_shards.size() != 0U raw Cache file exists already; Is there another DMatrix with the same cache prefix? Otherwise please remove it manually. /Users/runner/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) info.name_shards.size() != 0U finfo->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic) tmagic == kMagic invalid format, magic number mismatch Check failed: fi->Read(&format) Invalid page format /Users/runner/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 Check failed: mutex_.try_lock() Multiple threads attempting to use prefetcher /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/ellpack_page.cc Internal Error: XGBoost is not compiled with CUDA but EllpackPage is required .ellpack.page /Users/runner/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/work/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.cc Check failed: (std::is_same<AdapterT, CSCAdapter>::value) Expecting CSCAdapter Check failed: param != BatchParam{} Batch parameter is not initialized. param.gpu_id >= 0 param.max_bin >= 2 Check failed: in_stream->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic) invalid input file format /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/./simple_batch_iterator.h Check failed: page_ != nullptr /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.cc /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.h Check failed: source_ != nullptr .col.page Writing to CSCPageSource: Finished writing to .sorted.col.page SortedCSCPageSource: Finished writing to /Users/runner/work/ml-builds/ml-builds/xgboost/src/data/./sparse_page_dmatrix.h Slicing DMatrix is not supported for external memory. Raw binary data format. /Users/runner/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/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.h /Users/runner/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/2.262.1/work/ml-builds/ml-builds/xgboost/src/gbm/../common/common.h /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.h fi->Read(¶m_, sizeof(param_)) == sizeof(param_) DoBoost PredictBatch ntree_limit == 0U GBLinear::Predict ntrees is only valid for gbtree predictor PredictBatchInternal base_margin.size() == nsize * ngroup /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/include/xgboost/gbm.h Inplace predict is not supported by current booster. gblinear does not support prediction of leaf index GBLinear::PredictContribution: ntrees is only valid for gbtree predictor { "bias": [ , ], "weight": [ ] } bias:
+ : /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/../common/common.h /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear_model.h fi->Read(¶m_, sizeof(param_)) == sizeof(param_) DoBoost PredictBatch ntree_limit == 0U GBLinear::Predict ntrees is only valid for gbtree predictor PredictBatchInternal base_margin.size() == nsize * ngroup /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/gbm.h Inplace predict is not supported by current booster. gblinear does not support prediction of leaf index GBLinear::PredictContribution: ntrees is only valid for gbtree predictor { "bias": [ , ], "weight": [ ] } bias:
weight:
- gblinear_train_param Check failed: this->updater_ DeprecatedGBLinearModelParam /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/gbm/gbm.cc Unknown gbm type cpu_predictor GBTree /Users/runner/runners/2.262.1/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: Check failed: !updaters_.front()->CanModifyTree() Updater: ` ` can not be used to create new trees. Set `process_type` to `update` if you want to update existing trees. Check failed: up->CanModifyTree() can not be used to modify existing trees. Set `process_type` to `default` if you want to build new trees. model_.trees.size() < model_.trees_to_update.size() No more tree left for updating. For updating existing trees, boosting rounds can not exceed previous training rounds gpair->Size() == p_fmat->Info().num_row_ Mismatching size between number of rows from input data and size of gradient vector. CommitModel gbtree get<String>(in["name"]) == "gbtree" gbtree_train_param Loading from a raw memory buffer on CPU only machine. Changing predictor to auto. predictor tree_method Loading from a raw memory buffer on CPU only machine. Changing tree_method to hist. specified_updater default process_type Check failed: configured_ Check failed: cpu_predictor_ Data is on CUDA device, but XGBoost is not compiled with CUDA support. GBTreeModelParam GBTreeTrainParam DartTrainParam Tree booster, gradient boosted trees. dart Tree booster, dart. /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.h 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. 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. 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/2.262.1/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.cc param.num_trees == static_cast<int32_t>(trees.size()) fi->Read(¶m, sizeof(param)) == sizeof(param) 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 num_round CONFIG-offset: Learner /Users/runner/runners/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/include/xgboost/generic_parameters.h
+ gblinear_train_param Check failed: this->updater_ DeprecatedGBLinearModelParam /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbm.cc Unknown gbm type cpu_predictor GBTree /Users/runner/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: Check failed: !updaters_.front()->CanModifyTree() Updater: ` ` can not be used to create new trees. Set `process_type` to `update` if you want to update existing trees. Check failed: up->CanModifyTree() can not be used to modify existing trees. Set `process_type` to `default` if you want to build new trees. model_.trees.size() < model_.trees_to_update.size() No more tree left for updating. For updating existing trees, boosting rounds can not exceed previous training rounds gpair->Size() == p_fmat->Info().num_row_ Mismatching size between number of rows from input data and size of gradient vector. CommitModel gbtree get<String>(in["name"]) == "gbtree" gbtree_train_param Loading from a raw memory buffer on CPU only machine. Changing predictor to auto. predictor tree_method Loading from a raw memory buffer on CPU only machine. Changing tree_method to hist. specified_updater default process_type Check failed: configured_ Check failed: cpu_predictor_ Data is on CUDA device, but XGBoost is not compiled with CUDA support. GBTreeModelParam GBTreeTrainParam DartTrainParam Tree booster, gradient boosted trees. dart Tree booster, dart. /Users/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.h 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. 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. 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 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/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree_model.cc param.num_trees == static_cast<int32_t>(trees.size()) fi->Read(¶m, sizeof(param)) == sizeof(param) 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 num_round CONFIG-offset: Learner /Users/runner/work/ml-builds/ml-builds/xgboost/src/learner.cc Check failed: IsA<Object>(in) learner learner_model_param objective gradient_booster booster attributes num_feature num_class base_score Check failed: !this->need_configuration_ Call Configure before saving model. Configure /Users/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/generic_parameters.h
n_gpus: n_gpus Check failed: matrix.first Check failed: !matrix.second.ref.expired() 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.
- 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. learner_model_param_.num_feature == p_fmat->Info().num_col_ Number of columns does not match number of features in booster. Check failed: gbm_ != nullptr Predict must happen after Load or configuration BoostOneIter EvalOneIter multiple_predictions <= 1 Perform one kind of prediction at a time. value margin Unsupported prediction type: 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 ; learner_train_param generic_param Model Config fp.Read(&header[0], header.size()) == serialisation_header_.size() Check failed: header == serialisation_header_
+ 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. learner_model_param_.num_feature == p_fmat->Info().num_col_ Number of columns does not match number of features in booster. learner_model_param_.num_feature >= p_fmat->Info().num_col_ Check failed: gbm_ != nullptr Predict must happen after Load or configuration BoostOneIter EvalOneIter multiple_predictions <= 1 Perform one kind of prediction at a time. value margin Unsupported prediction type: 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 multi: metrics Loading model from XGBoost < 1.0.0, consider saving it again for improved compatibility rabit_bootstrap_cache ; 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:
@@ -4898,30 +5774,30 @@
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.
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/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.h unknown coordinate selector: _idx < size() UpdateFeature Update linear model according to shotgun coordinate descent algorithm. /Users/runner/runners/2.262.1/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: 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/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/src/metric/metric.cc Unknown metric function Cannot find a GPU metric builder for metric . Resorting to the CPU builder merror Multiclass classification error. mlogloss Multiclass negative loglikelihood. /Users/runner/runners/2.262.1/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/2.262.1/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() EvalRank: group structure must match number of prediction Cox metric does not support distributed evaluation aft-nloglik Negative log likelihood of Accelerated Failure Time model. aft_loss_param /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/metric/survival_metric.cc info.labels_lower_bound_.Size() != 0U y_lower cannot be empty info.labels_upper_bound_.Size() != 0U y_higher cannot be empty preds.Size() == info.labels_lower_bound_.Size() preds.Size() == info.labels_upper_bound_.Size() yhat.size() <= static_cast<size_t>(std::numeric_limits<omp_ulong>::max()) yhat is too big survival:aft AFT loss function /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/objective/aft_obj.cc binary:hinge Hinge loss. Expects labels to be in [0,1f] /Users/runner/runners/2.262.1/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/2.262.1/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/2.262.1/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). _offset < size() || size() == 0 (_count == dynamic_extent) || (_offset + _count <= size()) (index_ + n) <= span_->size() span_ == rhs.span_ Objective candidate: /Users/runner/runners/2.262.1/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/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/src/objective/regression_obj.cu Label set is empty. Loss: 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/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.cc tree_begin == 0 predts->version >= tree_begin predts->version == 0 output_groups != 0 ntree_limit != 0 beg_version <= end_version delta <= model.trees.size() Check failed: out_preds->Size() == output_groups * dmat->Info().num_row_ || out_preds->Size() == dmat->Info().num_row_ 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 = out_preds->size() == p_fmat->Info().num_row_ * model.learner_model_param->num_output_group model.param.size_leaf_vector == 0 Data type is not supported by CPU Predictor. m.NumColumns() == model.learner_model_param->num_feature Number of columns in data must equal to trained model. /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/any.h Check failed: type_ != nullptr The any container is empty requested= Check failed: *(type_->ptype_info) == typeid(T) The stored type mismatch stored= ncolumns != 0 /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/predictor/predictor.cc Check failed: container_.find(m) != container_.cend() Check failed: container_.at(m).ref.lock() [Internal error]: DMatrix: has expired. Unknown predictor type unordered_map::at: key not found /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/constraints.cc Failed to parse feature interaction constraint:
+ This can be done using Dask or Spark. See documentation for details. /Users/runner/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/work/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.h unknown coordinate selector: _idx < size() UpdateFeature Update linear model according to shotgun coordinate descent algorithm. /Users/runner/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: 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. mphe Mean Pseudo Huber 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/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/work/ml-builds/ml-builds/xgboost/src/metric/metric.cc Unknown metric function Cannot find a GPU metric builder for metric . Resorting to the CPU builder merror Multiclass classification error. mlogloss Multiclass negative loglikelihood. /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/multiclass_metric.cu preds.Size() == 0 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/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= info.labels_.Size() != 0U label set cannot be empty 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() EvalRank: group structure must match number of prediction Cox metric does not support distributed evaluation aft-nloglik Negative log likelihood of Accelerated Failure Time model. interval-regression-accuracy aft_loss_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/metric/survival_metric.cu Unknown probability distribution info.labels_lower_bound_.Size() != 0U labels_lower_bound cannot be empty info.labels_upper_bound_.Size() != 0U labels_upper_bound cannot be empty preds.Size() == info.labels_lower_bound_.Size() preds.Size() == info.labels_upper_bound_.Size() ndata == labels_upper_bound.Size() Check failed: metric_ AFT metric must be configured first, with distribution type and scale survival:aft AFT loss function /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/aft_obj.cu info.labels_lower_bound_.Size() == ndata info.labels_upper_bound_.Size() == ndata info.weights_.Size() == ndata Number of weights should be equal to number of data points. Unrecognized distribution /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/../common/transform.h Not part of device code. WITH_CUDA: binary:hinge Hinge loss. Expects labels to be in [0,1f] /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/hinge.cu labels are not correctly provided preds.size= , label.size= 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/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). (_count == dynamic_extent) ? (_offset <= size()) : (_offset + _count <= size()) (index_ + n) <= span_->size() span_ == rhs.span_ Objective candidate: /Users/runner/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/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. Regression Pseudo Huber error. 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 reg:pseudohubererror binary:logistic binary:logitraw scale_pos_weight Scale the weight of positive examples by this factor reg_loss_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/objective/regression_obj.cu Label set is empty. Loss: 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/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/work/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.cc tree_begin == 0 predts->version >= tree_begin predts->version == 0 output_groups != 0 ntree_limit != 0 beg_version <= end_version delta <= model.trees.size() Check failed: out_preds->Size() == output_groups * dmat->Info().num_row_ || out_preds->Size() == dmat->Info().num_row_ 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 = out_preds->size() == p_fmat->Info().num_row_ * model.learner_model_param->num_output_group model.param.size_leaf_vector == 0 Data type is not supported by CPU Predictor. m->NumColumns() == model.learner_model_param->num_feature Number of columns in data must equal to trained model. /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/any.h Check failed: type_ != nullptr The any container is empty requested= Check failed: *(type_->ptype_info) == typeid(T) The stored type mismatch stored= ncolumns != 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/predictor/predictor.cc Check failed: container_.find(m) != container_.cend() Check failed: container_.at(m).ref.lock() [Internal error]: DMatrix: has expired. Unknown predictor type unordered_map::at: key not found /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/constraints.cc Failed to parse feature interaction constraint:
With error:
- newsize != 0 /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/param.cc std::floor(d) == d Found floating point number in interaction constraints Unknown value type for interaction constraint: /Users/runner/runners/2.262.1/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/2.262.1/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 parent != RegTree::kInvalidNodeId 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. num_deleted 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. sampling_method gradient_based Sampling method. 0: select random training instances uniformly. 1: select random training instances with higher probability when the gradient and hessian are larger. (cf. CatBoost) 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}
+ newsize != 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/param.cc std::floor(d) == d Found floating point number in interaction constraints Unknown value type for interaction constraint: /Users/runner/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/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 parent != RegTree::kInvalidNodeId 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. num_deleted 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. sampling_method gradient_based Sampling method. 0: select random training instances uniformly. 1: select random training instances with higher probability when the gradient and hessian are larger. (cf. CatBoost) 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:
- /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./json.h ch == '{' Error at , Expect '{' but get ' Line , around ^` ` ch == ',' , 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}]
+ /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./json.h ch == '{' Error at , Expect '{' but get ' Line , around ^` ` ch == ',' , 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/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/tree_updater.cc Unknown tree updater ColMakerTrainParam grow_colmaker Grow tree with parallelization over columns. opt_dense_col EXP Param: speed optimization for dense column. train_param colmaker_train_param /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/updater_colmaker.cc Updater `grow_colmaker` or `exact` tree method doesn't support distributed training. seed Check failed: param_.cache_opt Support for `cache_opt' is removed in 1.0.0 fmat.Info().num_row_ == position_.size() param_.sampling_method == TrainParam::kUniform Only uniform sampling is supported, gradient-based sampling is only support by GPU Hist. /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/../common/random.h features.size() > 0 /Users/runner/runners/2.262.1/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= grow_local_histmaker Tree constructor that uses approximate histogram construction. grow_histmaker Tree constructor that uses approximate global of histogram construction. /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/../common/quantile.h 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/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/updater_histmaker.cc Check failed: param_.max_depth > 0 max_depth must be larger than 0 /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/./updater_basemaker-inl.h 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/2.262.1/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() prune Pruner that prune the tree according to statistics. /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/updater_prune.cc tree pruning end, extra nodes, pruned nodes, max_depth= Check failed: !tree[pid].IsLeaf() 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/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.cc out_preds.size() > 0U 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 EvaluateSplits upper_bound < static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) ApplySplit InitNewNode grow_fast_histmaker (Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram. Grow tree using quantized histogram. /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/../common/column_matrix.h gmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_val gmat_bin_size == kUint32BinsTypeSize bins_type_size_ == kUint32BinsTypeSize Quantile::Builder /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/../common/hist_util.h row_ptr_[nid] != kMax SubtractionTrick row_ptr_[nid] == kMax nodes == targeted_hists.size() /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/../common/threading_utils.h i < first_dimension_.size() hist_total == hist_memory_.size() /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/src/tree/../common/row_set.h elem_of_each_node_.size() == 0U Check failed: e.begin != nullptr n_left + n_right == e.Size() begin + n_left <= e.end begin + n_left + n_right == e.end begin < end end > begin nid < nodes_ i < ranges_.size() tid < nthreads_ Check failed: (*p_last_tree_)[nid].IsLeaf() 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()) data_ || size_ == 0 grow_fast_histmaker is deprecated, use grow_quantile_histmaker instead. refresh Refresher that refreshes the weight and statistics according to data. /Users/runner/runners/2.262.1/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/2.262.1/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/2.262.1/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/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.h finish reading at /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data.cc Unknown data type /Users/runner/runners/2.262.1/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.h param_.format == "libsvm" /Users/runner/runners/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.h cannot call ParseNext /Users/runner/runners/2.262.1/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/2.262.1/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/2.262.1/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/2.262.1/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/2.262.1/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/2.262.1/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/2.262.1/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.cc Check failed: begin != end /Users/runner/runners/2.262.1/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/2.262.1/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/2.262.1/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/2.262.1/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 Successfully deleted temporary directory ~TemporaryDirectory(): Could not remove temporary directory /Users/runner/runners/2.262.1/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/2.262.1/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
+{nodes}} {rankdir} {graph_attrs} /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/tree_updater.cc Unknown tree updater ColMakerTrainParam grow_colmaker Grow tree with parallelization over columns. opt_dense_col EXP Param: speed optimization for dense column. train_param colmaker_train_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_colmaker.cc Updater `grow_colmaker` or `exact` tree method doesn't support distributed training. seed Check failed: param_.cache_opt Support for `cache_opt' is removed in 1.0.0 fmat.Info().num_row_ == position_.size() param_.sampling_method == TrainParam::kUniform Only uniform sampling is supported, gradient-based sampling is only support by GPU Hist. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/random.h features.size() > 0 /Users/runner/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= grow_local_histmaker Tree constructor that uses approximate histogram construction. grow_histmaker Tree constructor that uses approximate global of histogram construction. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/quantile.h check quantile stats, nbig= , n= srcsize= , maxsize= , range= , chunk= Check failed: nbig < n quantile: too many large chunk ] rmin= , rmax= , wmin= , v= /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_histmaker.cc Check failed: param_.max_depth > 0 max_depth must be larger than 0 /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/./updater_basemaker-inl.h 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/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() prune Pruner that prune the tree according to statistics. TreePruner PrunerUpdate /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_prune.cc tree pruning end, extra nodes, pruned nodes, max_depth= Check failed: !tree[pid].IsLeaf() Check failed: nodes_[nodes_[rid].LeftChild() ].IsLeaf() Check failed: nodes_[nodes_[rid].RightChild()].IsLeaf() nid >= 1 Quantile::Builder Update SubtractionTrick UpdatePredictionCache /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.cc out_preds.size() > 0U 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 EvaluateSplits ApplySplit upper_bound < static_cast<uint32_t>(std::numeric_limits<int32_t>::max()) InitNewNode BuildLocalHistograms SplitSiblings BuildNodeStats ExpandWithLossGuide CPUHistMakerTrainParam GmatInitialization grow_fast_histmaker (Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram. Grow tree using quantized histogram. /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/row_set.h elem_of_each_node_.size() == 0U Check failed: e.begin != nullptr n_left + n_right == e.Size() begin + n_left <= e.end begin + n_left + n_right == e.end /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/column_matrix.h gmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid] <= max_val gmat_bin_size == kUint32BinsTypeSize bins_type_size_ == kUint32BinsTypeSize cpu_hist_train_param /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/./updater_quantile_hist.h Attempted to load interal configuration for a model file that was generated by a previous version of XGBoost. A likely cause for this warning is that the model was saved with saveRDS() in R or pickle.dump() in Python. We strongly ADVISE AGAINST using saveRDS() or pickle.dump() so that the model remains accessible in current and upcoming XGBoost releases. Please use xgb.save() instead to preserve models for the long term. For more details and explanation, see https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html single_precision_histogram Use single precision to build histograms. SyncHistograms SyncHistogramsAllreduce /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/threading_utils.h begin < end /Users/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/hist_util.h end > begin nid < nodes_ i < first_dimension_.size() i < ranges_.size() AddHistRows row_ptr_[nid] == kMax Check failed: (*p_last_tree_)[nid].IsLeaf() row_ptr_[nid] != kMax 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()) nodes == targeted_hists.size() hist_total == hist_memory_.size() tid < nthreads_ data_ || size_ == 0 grow_fast_histmaker is deprecated, use grow_quantile_histmaker instead. QuantileHistMaker refresh Refresher that refreshes the weight and statistics according to data. /Users/runner/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/work/ml-builds/ml-builds/xgboost/src/tree/updater_skmaker.cc qexpand_.size() != 0U Syncher that synchronize the tree in all distributed nodes. 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
@@ -4945,681 +5821,624 @@
[%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
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+ Read pickle string not implemented DataType does not support bitwise or operation 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/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/disk_row_iter.h Check failed: TryLoadCache() failed to build cache file /Users/runner/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/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.h finish reading at /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data.cc Unknown data type /Users/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.h param_.format == "libsvm" /Users/runner/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/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.h cannot call ParseNext /Users/runner/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/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() hdfs:// viewfs:// /Users/runner/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/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 /Users/runner/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/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/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.cc Check failed: begin != end /Users/runner/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/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/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 C /Users/runner/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 Successfully deleted temporary directory ~TemporaryDirectory(): Could not remove temporary directory /Users/runner/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/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) L P XQ ! 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І StringEv ~ObjectEv NumberEv Ъ Json data tree 4 aSERKS0_ LoadE DumpES0_PNSt3__11 NS_10StringViewE PNS_10JsonReaderE 3basic_ostreamIcNS1_11char_traitsIcEEEEb 2basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEb 3 7 Á PDFEd CDFEd GradPDFEd ߁HessPDFEd 3 7 PDFEd CDFEd GradPDFEd HessPDFEd 3 ˂7 PDFEd ߂CDFEd GradPDFEd HessPDFEd AFTLoss Monitor 4LossEdddd 8GradientEdddd 7HessianEdddd 5StartERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 4StopERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 21CollectFromOtherRanksEv ݆15PrintStatisticsERKNSt3__13mapINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEENS2_4pairImmEENS2_4lessIS9_EENS7_INSA_IKS9_SB_EEEEEE 5PrintEv axE inE mEEvPKvPviRKN3MPI8DatatypeE yEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE Version ̉DMatrix эLearner RegTree 4 6StringERKNSt3__15tupleIJiiiEEE 8kInvalidE LoadE S Ŋ RKNS_4JsonEb PN4dmlc6StreamE a ՊelfEv veEPN meERKNSt3__15tupleIJiiiEEE S_4JsonE 4dmlc6StreamE Ђ Ў Д 7xgboost S_16ParserFactoryRegI 4 1 Ӫ9MetricRegEE3GetEv data19SparsePageFormatRegINS1_ ˌtree17SplitEvaluatorRegEE3GetEv 1 7CSCPageEEEE3GetEv 0SparsePageEEEE3GetEv 3SortedCSCPageEEEE3GetEv ō1EllpackPageEEEE3GetEv ˍ 6CreateINS_4data1 4LoadERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEbbS9_m 2DenseAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm ɑ0CS ϑ6DataTableAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 1FileAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 5IteratorAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm RAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm CAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm Ь 5ClearEv 10LoadBinaryEPN4dmlc6StreamE 7SetInfoEPKc 9kNumFieldE 10SaveBinaryEPN4dmlc6StreamE ߔ5SliceENS_6common4SpanIKiLm18446744073709551615EEE 8ValidateEi ԕ б PKvNS_8DataTypeEm ΕRKNSt3__112basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEE ڕ л 4PushERKS0_ 7PushCSCERKS0_ 7xgboost4data16SparsePageWriterINS7_10SparsePageEEC1ERKNS_6vectorINS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEENSG_ISI_EEEESM_mEUlvE_EEEEEPvSP_ ̗4dmlc җ 12ThreadedIterIN 4data14TextParserBaseI 7xgboost S 1 7CSCPageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ 0SparsePageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ 3SortedCSCPageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ C D 12SetBaseRowIdEm 2E 1E ݚ v ךPNS_7DMatrixERKNS_10BatchParamE v PNS_7DMatrixERKNS_10BatchParamE 2Ev 1Ev 1 49__dmlc_registry_file_tag_sparse_page_raw_format__Ev 7 3SimpleDMatrix EllpackPageSourceC ǜSparsePageDMatrix Х 2EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE 1EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE C 4InfoEv ܢ5SliceENS_6common4SpanIKiLm18446744073709551615EEE 1 22GetSortedColumnBatchesEv 2 1 INS0_1 EPN4dmlc6StreamE 2DenseAdapterEEEPT_fi 0CS ̡6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi Ģ5IteratorAdapterEEEPT_fi Т INS0_1 ӠEPN4dmlc6StreamE 2DenseAdapterEEEPT_fi ơ0CS 6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi ʢ5IteratorAdapterEEEPT_fi ֢ RAdapterEEEPT_fi CAdapterEEEPT_fi RAdapterEEEPT_fi CAdapterEEEPT_fi Р data1 tree14SplitEvaluator17ComputeSplitScoreEjjRKNS0_9GradStatsES4_ 3SimpleDMatrix4InfoEv 7SparsePageDMatrix4InfoEv 3GetRowBatchesEv 6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE 5SaveToLocalFileERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE ĥ 4InfoEv 1 22GetSortedColumnBatchesEv 3GetRowBatchesEv 6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE gbm obj 2FeatureInteractionConstraintHost 3 1 28DeprecatedGBLinearModelParam11__MANAGER__Ev ͪ6GBTree ī 5__dmlc_registry_file_tag_gblinear__Ev ݨ3__dmlc_registry_file_tag_gbtree__Ev 8GBLinearTrainParam11__MANAGER__Ev 3GBLinearModel9LoadModelERKNS_4JsonE Ǫ6GBTree 4DartTrainParam11__MANAGER__Ev 1GBTreeModel 1 6GBTree ٵ 3GBLinearModel9SaveModelEPNS_4JsonE 1GBTreeModel " " " 8GradientBoosterRegEE3GetEv 6LinearUpdaterRegEE3GetEv 2 4 0TreeGenRegEE3GetEv # Ѕ# # 9 Ǭ1 ߭2 7DoBoostEPNS_7DMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_20PredictionCacheEntryE ConfigureERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE ٭LoadModelERKNS_4JsonE ۶ # 7ConfigureUpdatersEv 1 3BoostNewTreesEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEiPNSt3__16vectorINSA_10unique_ptrINS_7RegTreeENSA_14default_deleteISD_EEEENSA_9allocatorISG_EEEE 0LoadConfigERKNS_4JsonE 2PredictBatchEPNS_7DMatrixEPNS_20PredictionCacheEntryEbj # InitUpdaterERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE CommitModelEONSt3__16vectorINS3_INS2_10unique_ptrINS_7RegTreeENS2_14default_deleteIS5_EEEENS2_9allocatorIS8_EEEENS9_ISB_EEEEPNS_7DMatrixEPNS_20PredictionCacheEntryE # 2ConfigureWithKnownDataERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEEPNS_7DMatrixE 6PerformTreeMethodHeuristicEPNS_7DMatrixE # # # # # # hn S I VN 8_N 16_N7xgboost7LearnerD 7xgboost K7xgboost3gbm6GBTree10SaveConfigEPNS_4JsonE ն 3gbm6GBTree10LoadConfigERKNS_4JsonE ӵ7LearnerD $ 1 9SaveModelEPNS_4JsonE 0SaveConfigEPNS_4JsonE ϶2GetPredictorEPKNS_16HostDeviceVectorIfEEPNS_7DMatrixE С$ к$ $ $ $ $ ModelParam11__MANAGER__Ev TrainParam11__MANAGER__Ev $ $ $ 4SaveEPN4dmlc6StreamE 9SaveModelEPNS_4JsonE І( 4LoadEPN4dmlc6StreamE 9LoadModelERKNS_4JsonE Њ( ( ( Learner19AllowLazyCheckPointEv RegTree ( D й6CreateERKNSt3__16vectorINS1_10shared_ptrINS_7DMatrixEEENS1_9allocatorIS5_EEEE 2Ev 1Ev 0Ev ( ( 1Ev 0Ev ( 1Ev 0Ev ( ( ( ( ModelParamC ߺTrainParam11__MANAGER__Ev 2ERKNS_23LearnerModelParamLegacyEf 1ERKNS_23LearnerModelParamLegacyEf ( ( 3LearnerModelParamLegacy11__MANAGER__Ev 6ParseInteractionConstraintERKNSt3__112basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEEPNS0_6vectorINS9_IjNS4_IjEEEENS4_ISB_EEEE 0LearnerConfiguration11kEvalMetricE ( ( 1 6kCpuIdE 1__MANAGER__Ev 4ConfigureGpuIdEb ( ( ( , / LinearUpdater6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE ConsoleLogger Tr GraphvizParam11__MANAGER__Ev / 1 4 6LinearTrainParam11__MANAGER__Ev 5CoordinateParam11__MANAGER__Ev / / 5__dmlc_registry_file_tag_updater_coordinate__Ev 2__dmlc_registry_file_tag_updater_shotgun__Ev / 1 6CustomLogMessage3LogERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE 2 0 ߜ8TemporaryDirectory15RecursiveDeleteERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE ب 1 D 9 1 C 6param_E 2Ev 1Ev 1 ShouldLogENS0_12LogVerbosityE ConfigureERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEE н1 1 ackerLoggerD eeGenerator 2Ev 1Ev 1 1 1 1 6DefaultVerbosityEv 5GlobalVerbosityEv 7global_verbosity_E 1 1 2E 1E NS0_12LogVerbosityE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE 1 NS0_12LogVerbosityE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEiNS0_12LogVerbosityE 1 1 1 4 3 2 5__dmlc_registry_file_tag_elementwise_metric__Ev 4__dmlc_registry_file_tag_multiclass_metric__Ev 2__dmlc_registry_file_tag_survival_metric__Ev 1 1 3 3 3 MetricGPURegEE3GetEv PredictorRegEE3GetEv 3 3 8__dmlc_registry_file_tag_rank_metric__Ev 5__make_MetricReg_PossionNegLoglik__E 2__make_MetricReg_GammaDeviance__E 1__make_MetricReg_ 3__make_MetricReg_TweedieNLogLik__E 4 5 7 3 41__dmlc_registry_file_tag_ 22 1 9ListEntry7CmpPredERKS1_S3_ 4__dmlc_registry_file_tag_aft_obj__Ev 6__dmlc_registry_file_tag_hinge_obj__Ev 5__dmlc_registry_file_tag_rank_obj__Ev 7 7 multiclass_obj__Ev regression_obj__Ev 8 SoftmaxMultiClassParam11__MANAGER__Ev PoissonRegressionParam11__MANAGER__Ev TweedieRegressionParam11__MANAGER__Ev 8 ObjFunctionRegEE3GetEv TreeUpdaterRegEE3GetEv 9 9 9 5LambdaRankParam11__MANAGER__Ev 2RegLossParam11__MANAGER__Ev 9 9 ; ; ; ; 40__dmlc_registry_file_tag_cpu_predictor__Ev 9PredValueERKNS_6common4SpanIKNS_5EntryELm18446744073709551615EEERKNSt3__16vectorINS8_10unique_ptrINS_7RegTreeENS8_14default_deleteISB_EEEENS8_9allocatorISE_EEEERKNS9_IiNSF_IiEEEEiPNSB_4FVecEjj м? ? A 19ClearExpiredEntriesEv 5 9ContainerEv A CacheENSt3__110shared_ptrINS_7DMatrixEEEi EntryEPNS_7DMatrixE A A A 9ConfigureERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEE 6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE A A 9 5ResetEv ConfigureERKNS_4tree10TrainParamEj SplitImplEijii A A B B B B 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 B B B B B C C C 6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS_10FeatureMapEb 5MatchERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS1_3mapIS7_S7_NS1_4lessIS7_EENS5_INS1_4pairIS8_S7_EEEEEE C C 9 5EqualERKS0_ 1 4SaveEPN4dmlc6StreamE 2 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6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEE 21UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE 7Builder R R R 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 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fEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ iEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ xEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ ] ^ _ ` b j ʔy fE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjfEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ iE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjiEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ xE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjxEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ Κc 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_ ȚxE8FillDataEPNS_6vectorINS8_17RowBlockContainerIyxEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ Ԛd e g g Ўh h 1 23IndexedRecordIOSplitter 0FileSystem ޛ2LineSplitter1 6RecordIOSplitter1 4InputSplitBase 5LocalFileSystem ި 11GetInstanceERKNS0_3URIE ٜ22ListDirectoryRecursiveERKNS0_3URIEPNSt3__16vectorINS0_8FileInfoENS5_9allocatorIS7_EEEE Ҩ h InputSplit6CreateEPKc SeekStream13CreateForReadEPKcb ɝ jjS2_ S2_jjS2_bimb h h i i 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 Ƣ1 j j k Љk k ReadChunkEPvPm Next k ChunkEPNS_10InputSplit4BlobE BatchEPNS_10InputSplit4BlobEm k NextBatchExEPNS0_14InputSplitBase5ChunkEm BeforeFirstEv k Сk k 4 1 D ݧ8StripEndENSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEc 9ReadChunkEPvPm 5Chunk InitEPNS0_10FileSystemEPKcmb ReadEPvm k 7InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb ˧4ResetPartitionEjj ѧ1BeforeFirstEv ק3ConvertToURIsERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 6ExtractNextChunkEPNS_10InputSplit4BlobEPNS1_5ChunkE ̨ k k k 2Ev 1Ev 0Ev k k k k k k l 4LoadEPS1_m 6AppendEPS1_m ƨ l l l o o 1 4OpenERKNS0_3URIEPKcb 1 ש3ListDirectoryERKNS0_3URIEPNSt3__16vectorINS0_8FileInfoENS5_9allocatorIS7_EEEE GetPathInfoERKNS0_3URIE OpenForReadERKNS0_3URIEb o o o o 1 Ѫ4InitEiPPc ݼ8FinalizeEv 9 3AllreduceBase 5AllreduceRobust 2 û1DataRequestERKNSt3__14pairIbiEERKNS1_6vectorIcNS1_9allocatorIcEEEEm 0Allreduce_EPvmmPFvPKvS1_iRKN3MPI8DatatypeEENS0_3mpi8DataTypeENSA_6OpTypeEPFvS1_ES1_PKciSG_ C 4InitEiPPc 1 8S ӭ20TryReduceScatterRingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE 2Ev 1Ev p p p 4ReConnectLinksEPKc ͭ2Tr 6TryAll p hutdownEv etParamEPKcS3_ ޮ p p ackerPrintERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE خy p p AllreduceEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE BroadcastEPvmi q reduce ͯgatherRingEPvmmmm RingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE TreeEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE q Њq q q q C 4InitEiPPc 8S 1 9 20Try 2Ev 1Ev q utils c_api9All 5ErrorEPKcz ٱ6AssertEbPKcz ߱21STOP_PROCESS_ON_ERRORE r r r Ѝr hutdownEv etParamEPKcS3_ Аr 1 7 5 4 3 6TryDecideRoutingENS1_11RecoverTypeEPmPiPNSt3__16vectorIbNS5_9allocatorIbEEEE 2TryGetResultEPvmib ˼ R ͳCheckPoint_EPKN4dmlc12SerializableES5_b ecoverExecEPvmiiiPKc ingPassingEPvmmmmPNS0_13AllreduceBase10LinkRecordES5_ r r SetBootstrapCacheERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEPKvmm GetBootstrapCacheERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEPvmm TryLoadCheckPointEb зr r All BroadcastEPvmiPKciS4_ gatherEPvmmmmPKciS4_ reduceEPvmmPFvPKvS2_iRKN3MPI8DatatypeEEPFvS2_ES2_PKciSE_ r CheckAndRecoverENS0_13AllreduceBase10ReturnTypeE LocalModelCheckEb TryRestoreCacheEbii r r s LoadCheckPointEPN4dmlc12SerializableES4_ TryRecoverDataENS1_11RecoverTypeEPvmiRKNSt3__16vectorIbNS4_9allocatorIbEEEE s s s CheckinLocalStateEPNSt3__16vectorImNS2_9allocatorImEEEEPNS2_12basic_stringIcNS2_11char_traitsIcEENS4_IcEEEE RecoverLocalStateEPNSt3__16vectorImNS2_9allocatorImEEEEPNS2_12basic_stringIcNS2_11char_traitsIcEENS4_IcEEEE ż s TryResetLinksEv ActionSummary7ReducerEPKvPviRKN3MPI8DatatypeE Ѽ s s ShortestDistERKNSt3__14pairIbmEERKNS1_6vectorINS2_IimEENS1_9allocatorIS7_EEEEm ReduceHandle t t Хt t t t t t t u u GetEngineEv AllgatherEPvmmmmPKciS3_ u u u C D 8TypeSizeERKN3MPI8DatatypeE Ծ4InitEPFvPKvPviRKN3MPI8DatatypeEEm ھ9AllreduceEPvmmPFvS2_ES2_PKciS6_ 2Ev 1Ev u u 2Ev Ⱦ1Ev ξ u u u Чu u reduceEPvmNS_6engine3mpi8DataTypeENS3_6OpTypeEPFvS1_ES1_ gatherEPvmmmmi u u I Finalize Get TrackerPrint Broadcast All L CheckPoint VersionNumber nit sDistributed мu u R WorldSize ProcessorName ingPrevRank ank u u u нu u пu u gather reduce u u oadCheckPoint inkTag u u u u u u u u u cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE u u u u u u u u u u v v v cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE v v v v v v N ZN PF ؚF 7xgboost 4dmlc 5rabit St3__1 7 4 6 1 9 8JsonNullE 2 3 5 DMatrixE LearnerE RegTreeE ؐ data tree 1 6detail19SingleBatchDataIterINS0_ 2 5IteratorAdapterE 0CS 2DenseAdapterE 6 1FileAdapterE 3SimpleDMatrixE 7SparsePageDMatrixE 9SparsePageRawFormatINS_ 8DataIterIN 7istream 9parameter1 5ErrorE 1 6 4data 2io 7xgboost S ɝ 4data 1 7CSCPageEEE 1 21DataTableAdapterBatchEEE 6FileAdapterBatchEEE 5CS 7DenseAdapterBatchEEE ē RAdapterE CAdapterE 1 21DataTableAdapterBatchEEE 5CS 7DenseAdapterBatchEEE RAdapterBatchEEE CAdapterBatchEEE RAdapterBatchEEE CAdapterBatchEEE ؔ DataTableAdapterE SparsePageFormatINS_ ٗ 5 6engine utils1 c_api1 8MemoryBufferStreamE 9MemoryFixSizeBufferE ܘ E 5InBufE 2 1 6__ 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 emplaceIN7xgboost16HostDeviceVectorIjEENS_9allocatorIS3_EEEE 7xgboost S_13__empty_stateIcEENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 7DMatrixENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 1 8JsonNullENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 9JsonArrayENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE Հ
-4 9basic_ 5 3 7 0__ 8 1__ 6__ 2__match_charIcEE default_deleteIN basic_ifstreamIcNS_11char_traitsIcEEEE 7xgboost S_13__empty_stateIcEEEE 7DMatrixEEE 1 8JsonNullEEE 9JsonArrayEEE common linear metric MetricE Շ 1 9DenseCutsE 23ProbabilityDistributionE 0 1 6PeekableInStreamE 5FixedSizeStreamE 2LogisticDistE SparseCutsE NormalDistE CutsBuilderE ExtremeDistE 7BatchIteratorImplINS1_ 0 1Json 7CSCPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE 1 ߝ 7BatchIteratorImplINS1_ 0 1Json 7CSCPageEEEEE 1 ٞ 0SparsePageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE 3SortedCSCPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE 1EllpackPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE 0SparsePageEEEEE 3SortedCSCPageEEEEE 1EllpackPageEEEEE 0Json 1 7 5GradientBoosterE 2ConfigurableE 3 StringE ObjectE NumberE ReaderE WriterE JsonArrayE LearnerIOE predictor12CPUPredictorE PredictorE ̢ Json LearnerImplE ObjFunctionE TreeUpdaterE IntegerE BooleanE գ istringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE ostringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE ߐ basic_stringbufIcNS_11char_traitsIcEENS_9allocatorIcEEEE __ Json SparsePageENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE ObjectENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE NumberENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE StringENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE ֒ Json SparsePageEEE ObjectEEE NumberEEE StringEEE ݒڦ IntegerENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE BooleanENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE BooleanEEE IntegerEEE 9FixedPrecisionStreamContainerINSt3__19allocatorIcEEEE 0LearnerConfigurationE é Ȫ 0FieldEntryI 7FieldEntryNumericINS0_10FieldEntryI 4FieldEntryBaseINS0_10FieldEntryI 6FieldAccessEntryE N mEE bEE fEE jEE iEE dEE 7xgboost St3__1 6common27ProbabilityDistributionTypeEEE 1 Ԭ iEEiEE mEEmEE fEEfEE dEEdEE jEEjEE iEEiEE NSt3__1 mEEmEE fEEfEE bEEbEE dEEdEE jEEjEE basic_filebufIcNS_11char_traitsIcEEEE __ ٱ bad_function_callE __ 4ExternalMemoryPrefetcherINS_ 3S 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 2 0 ۀ ThreadedIterIN S RowBlockIterI 7xgboost S 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE copedThreadE erializableE ̴ function6__ l_anchorIcEE r_anchorIcEE back_refIcEE funcI baseIF ZN PF љ 7xgboost4 4dmlc ͠ data24ExternalMemoryPrefetcherINS2_ tree1 1 7CSCPageEEC1ERKNS3_9CacheInfoEEUl 0SparsePageEEC1ERKNS3_9CacheInfoEEUl 3SortedCSCPageEEC1ERKNS3_9CacheInfoEEUl PPS5_E_NS_9allocatorISC_EEFbSB_EEE vE_NS_9allocatorISA_EEFvvEEE b vvEEE PN7xgboost PPN N7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES6_EEE њ 7xgboost 4dmlc ɢS_6vectorIN4dmlc4data17RowBlockContainerI 1 7CSCPageEEEE 0SparsePageEEEE 3SortedCSCPageEEEE 7xgboost4 4dmlc data24ExternalMemoryPrefetcherINS_ tree1 ߖ 1 7CSCPageEEC1ERKNS0_9CacheInfoEEUl 0SparsePageEEC1ERKNS0_9CacheInfoEEUl 3SortedCSCPageEEC1ERKNS0_9CacheInfoEEUl PPS2_E_ vE_ impleBatchIteratorImplINS_ parseBatchIteratorImplINS0_24ExternalMemoryPrefetcherINS_ 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1EllpackPageEEE BatchIteratorImplINS_ GraphvizGeneratorE ϒ 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1EllpackPageEEE ʺ 1 7CSCPageEEES3_EE 0SparsePageEEES3_EE 3SortedCSCPageEEES3_EE 1EllpackPageEEES3_EE PPS5_E_NS_9allocatorISC_EEFbSB_EEE vE_NS_9allocatorISA_EEFvvEEE PPS2_E_ vE_ PPS5_E_NS_9allocatorISC_EEFbSB_EEE vE_NS_9allocatorISA_EEFvvEEE PPS2_E_ vE_ 4 1 6MetricEPKcEEE 9PredictorEPKNS2_16GenericParameterEEEE data16SparsePageFormatINS2_ tree14SplitEvaluatorENS_10unique_ptrIS4_NS_14default_deleteIS4_EEEEEEE 1 7CSCPageEEEvEEE 0SparsePageEEEvEEE 3SortedCSCPageEEEvEEE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEEE 6vectorIiNS2_9allocatorIiEEEEEE 12basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEEEES9_EE 6vectorIiNS3_9allocatorIiEEEEEES7_EE 5GradientBoosterEPKNS2_17LearnerModelParamEEEE 3 1 gbm obj Ċ 8GBLinearE 1 6GBTreeE 4DartE ModelE ValueE 3GBLinearModelE 1GBTreeModelE 5TreeProcessTypeEEE 3 0TreeMethodEEE PredictorTypeEEE DataSplitModeEEE StreamE πParserI SeekStreamE ParamErrorE InputSplitE LinearUpdaterEvEEE TreeGeneratorERKNS2_10FeatureMapENS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEEbEEE 1 ͂2 ƃ 7CoordinateUpdaterE 5FeatureSelectorE 4ShotgunUpdaterE LinearUpdaterE T ȑJsonGeneratorE Ȓ 1 ҃2 CyclicFeatureSelectorE GreedyFeatureSelectorE RandomFeatureSelectorE ShuffleFeatureSelectorE ThriftyFeatureSelectorE 1 7Eval 9EvalAucPRE lj8Eval Չ 3Eval ܅4Eval 6EvalMultiLogLossE EWiseBaseINS0_ PrecisionE Ή 1 20EvalPoissonNegLogLikEEE 9EvalErrorEEE 1EvalRowRMSEEEE χ2EvalRowRMSLEEEE ۇ0EvalRowMAEEEE 4EvalRowLogLossEEE 7EvalGammaDevianceEEE 6EvalGammaNLogLikEEE 8EvalTweedieNLogLikEEE M RankConfigE atchErrorE ĈClassBaseINS0_1 ʈ 4EvalMatchErrorEEE 6EvalMultiLogLossEEE A MAPE CoxE MSE ucE FTE RankE NDCGE Ă ߂ ObjFunctionEvEEE TreeUpdaterEvEEE 6AFTObjE 8HingeObjE 20SoftmaxMultiClassObjE 1 ̈ ∀ 3 ы0RegLossObjINS0_ 7 5GammaRegressionE َ LambdaRankObjINS0_2 CoxRegressionE Ҏ 8PairwiseLambdaWeightComputerEEE 4NDCGLambdaWeightComputerEEE 3MAPLambdaWeightComputerEEE 䐀 1 22LogisticClassificationEEE 6LinearSquareLossEEE 5SquaredLogErrorEEE 8LogisticRegressionEEE 1LogisticRawEEE ޒ 嗀 PoissonRegressionE ˎTweedieRegressionE 와 ՞ 䟀 1 8ColMaker 9 ԓ23GlobalProposalHistMakerE 4SplitEvaluatorE 0 9MonotonicConstraintE ʐ1 7QuantileHistMaker 3TreeRefresherE ˡ ElasticNetE ÐTreePrunerE ا 지 Ҩ ꨀ ੀ ݪ ޫ Ԭ 䮀 extGeneratorE reeGeneratorE 쯀 basic_stringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE __ ӳ 䴀 E 7BuilderE Ķ ݶ CQHistMakerE ͓SketchMakerE TreeSyncherE HistMakerE BaseMakerE 1CQHistMaker10CreateHistERKNS_6vectorINS2_6detail20GradientPairInternalIfEENS_9allocatorIS8_EEEEPNS2_7DMatrixERKNS5_IjNS9_IjEEEERKNS2_7RegTreeEEUlvE_NS9_ISN_EEFvvEEE ؖ3TreeRefresher6UpdateEPNS2_16HostDeviceVectorINS2_6detail20GradientPairInternalIfEEEEPNS2_7DMatrixERKNS_6vectorIPNS2_7RegTreeENS_9allocatorISF_EEEEEUlvE_NSG_ISL_EEFvvEEE ȹ 1CQHistMaker10CreateHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS2_9allocatorIS6_EEEEPNS_7DMatrixERKNS3_IjNS7_IjEEEERKNS_7RegTreeEEUlvE_ 3TreeRefresher6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEEEUlvE_ Ǿ 7BuilderE ÙE ʙ ˿ bN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES6_ENS_9allocatorIS8_EES7_EE ʚvvENS_9allocatorIS3_EES2_EE bN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_E vvE bN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_E vvE Ā ŀ ƀ ɀ ʀ 1 9CSVParserI 1 Ӝ2 4T 0ParserImplI DiskRowIterI LibFMParserI j y fEE iEE xEE ǭˀ j y fEE iEE xEE έˀ _ t3__16vectorINS_4data17RowBlockContainerI 8RowBlockI ʞ4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEE j ֞y fEEEE iEEEE xEEEE խˀ _ t3__16vectorINS_4data17RowBlockContainerI Ӳ 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEE j y fEEEE iEEEE xEEEE ܭˀ j y fEEEE ƠiEEEE xEEEE ̀ 4data1 2io1 1DiskRowIterI 4ThreadedParserI j y fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS3_17RowBlockContainerIjfEEE_NS_9allocatorISA_EEFbS9_EEE ¢vE_NS_9allocatorIS6_EEFvvEEE ̀ 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEEE Ⱦ j y fEEEEE iEEEEE xEEEEE Ү̀ 4data1 У2io1 Ͼ 1DiskRowIterI 4ThreadedParserI j y fE12TryLoadCacheEvEUl ФiE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl ٮ PPNS0_17RowBlockContainerIjfEEE_ vE_ π BasicRowIterI LibSVMParserI j ¥y fEE ٥iEE xEE Ѐ fEE iEE xEE Ѐ fEE iEE xEE Ѐ fEEEE iEEEE xEEEE Ѐ fEEEE ݦiEEEE xEEEE Ѐ fEEEE iEEEE xEEEE р fE12TryLoadCacheEvEUl էiE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl ů PPNS3_17RowBlockContainerIyfEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE р fEEEEE ݨiEEEEE xEEEEE Ҁ fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS0_17RowBlockContainerIyfEEE_ ީvE_ Ӏ Ԁ Ԁ fEE iEE xEE Հ Հ Հ Հ ր ր PPNS3_17RowBlockContainerIjiEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE ׀ PPNS0_17RowBlockContainerIjiEEE_ ЫvE_ ޫ ـ ڀ ڀ ڀ ڀ ۀ ۀ ۀ PPNS3_17RowBlockContainerIyiEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE ܀ ݀ PPNS0_17RowBlockContainerIyiEEE_ vE_ ݀ ހ ߀ ߀ PPNS3_17RowBlockContainerIjxEEE_NS_9allocatorISA_EEFbS9_EEE ˮvE_NS_9allocatorIS6_EEFvvEEE PPNS0_17RowBlockContainerIjxEEE_ vE_ PPNS3_17RowBlockContainerIyxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE PPNS0_17RowBlockContainerIyxEEE_ vE_ jfEE yfEE extParserBaseI hreadedParserI j ȱy fEE ߱iEE xEE j y ɷ fEE iEE xEE j y fEE iEE xEE jfEE ̲yfEE jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE jfEC1EPNS3_10ParserImplIjfEEEUl yfEC1EPNS3_10ParserImplIyfEEEUl PPNS_6vectorINS3_17RowBlockContainerIjfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE jfEENS_9allocatorIS6_EEEEEEE yfEENS_9allocatorIS6_EEEEEEE jfEC1EPNS0_10ParserImplIjfEEEUl yfEC1EPNS0_10ParserImplIyfEEEUl PPNSt3__16vectorINS0_17RowBlockContainerIjfEENS6_9allocatorIS9_EEEEE_ vE_ fEE ·iEE xEE ʻ fEE iEE xEE ѻ fEE iEE xEE ػ PPNS_6vectorINS3_17RowBlockContainerIyfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE PPNSt3__16vectorINS0_17RowBlockContainerIyfEENS6_9allocatorIS9_EEEEE_ vE_ jfEE yfEE j y Ѻ fEE ʺiEE xEE fEE iEE xEE û 1 23IndexedRecordIOSplitterE 5 ؼ8ThreadedInputSplitE 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_ ſ 、 ց CachedInputSplitE RecordIOSplitterE 4InitCachedIterEvEUl 5InitPreprocIterEvEUlPPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE PPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE vE_NS_9allocatorIS5_EEFvvEEE 4InitCachedIterEvEUl 5InitPreprocIterEvEUlPPNS0_14InputSplitBase5ChunkEE_ PPNS0_14InputSplitBase5ChunkEE_ vE_ Ƈ ߇ end_stateIcEE lookaheadIcNS_12regex_traitsIcEEEE alternateIcEE match_anyIcEE ˈ nodeIcEE loopIcEE 䈁 ۉ empty_stateIcEE assoc_stateIbEE owns_one_stateIcEE back_ref_icaseIcNS_12regex_traitsIcEEEE has_one_stateIcEE word_boundaryIcNS_12regex_traitsIcEEEE Ŋ ⊁ ċ match_char_icaseIcNS_12regex_traitsIcEEEE back_ref_collateIcNS_12regex_traitsIcEEEE ̌ Ѝ Ԏ owns_two_statesIcEE repeat_one_loopIcEE ؏ ystemE treamE ̐ 㐁 1 7IEngineE 3AllreduceBaseE 5AllreduceRobustE 葁 1ReadWrapperE 2WriteWrapperE Γ N ZN F PF 4dmlc 7xgboost St3__1 5rabit 5ErrorE 8DataIterIN 6 1 7istream 9parameter1 4data 2io 7 4 6 5 1 9 8JsonNullE 2 3 DMatrixE LearnerE RegTreeE 7xgboost S 4data 1 7CSCPageEEE 1 21DataTableAdapterBatchEEE 6FileAdapterBatchEEE 5CS 7DenseAdapterBatchEEE data tree 1 6detail19SingleBatchDataIterINS0_ 2 5IteratorAdapterE 0CS 2DenseAdapterE 6 1FileAdapterE 3SimpleDMatrixE 7SparsePageDMatrixE 9SparsePageRawFormatINS_ RAdapterBatchEEE CAdapterBatchEEE 1 21DataTableAdapterBatchEEE 5CS 7DenseAdapterBatchEEE RAdapterBatchEEE CAdapterBatchEEE RAdapterE CAdapterE DataTableAdapterE SparsePageFormatINS_ 1 2 6__
-9basic_ 5 8 4basic_ifstreamIcNS_11char_traitsIcEEEE 3 7 0__ 1__ 6__ 2__match_charIcEE ostringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE istringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE basic_stringbufIcNS_11char_traitsIcEENS_9allocatorIcEEEE __ 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 emplaceIN7xgboost16HostDeviceVectorIjEENS_9allocatorIS3_EEEE 7xgboost S_13__empty_stateIcEENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 1 7DMatrixENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 8JsonNullENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 9JsonArrayENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 0 7BatchIteratorImplINS1_ 1Json Json SparsePageENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE ObjectENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 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3 7GraphvizGenerator 4dmlc 7xgboost 5rabit .K 8St3__114__thread_proxyINS_5tupleIJNS_10unique_ptrINS_15__thread_structENS_14default_deleteIS3_EEEEZN 3any11TypeOnStackINSt3__110shared_ptrIN7xgboost4data1 8RegistryIN 1 4data1 6 2io у 2DenseAdapterEEEE 0CSRAdapterEEEE 7destroyEPNS0_4DataE 16create_from_dataEPNS0_4DataERKS9_ 7destroyEPNS0_4DataE 16create_from_dataEPNS0_4DataERKS9_ 6 1 39 8 4 מ7 ͥ5Entry8CmpValueERKS0_S2_ 3 2 detail1 common linear metric Metric6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE 6 9ToCharsUnsignedImplEPcS1_y 7FromCharFloatImplEPKciPf 4RyuPowLogUtils1 ToCharsFloatImplEfPc ItoaUnsignedImplEPcjy 1 21 8 9DenseCuts +5Index1 -7Monitor 2G 4AllVisibleGPUsEv 6 3 5 0SparseCuts *1CutsBuilder8UseGroupE ,8LoadSequentialFileENSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEb ̈́ lobalRandomEv HistBuilderI ! GHistIndexMatrix PeekableInStream 2 11ResizeIndexEmRKNS_10SparsePageEmmb )4InitEPNS_7DMatrixEi - 0SetIndexDataForDenseI 1SetIndexDataForSparseENS0_4SpanIjLm18446744073709551615EEEmRKNS_10SparsePageEmm ) hEEvNS0_4SpanIT_Lm18446744073709551615EEEmRKNS_10SparsePageEmNS3_IKjLm18446744073709551615EEEm tEEvNS0_4SpanIT_Lm18446744073709551615EEEmRKNS_10SparsePageEmNS3_IKjLm18446744073709551615EEEm jEEvNS0_4SpanIT_Lm18446744073709551615EEEmRKNS_10SparsePageEmNS3_IKjLm18446744073709551615EEEm InitilizeHistByZeroesI GHistIndexBlockMatrix4InitERKNS0_16GHistIndexMatrixERKNS0_12ColumnMatrixERKNS_4tree10TrainParamE - fEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEEmm dEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEEmm IncrementHistI HistogramCuts ) fEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_mm dEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_mm Љ CopyHistI AFTParam11__MANAGER__Ev Prefetch15kNoPrefetchSizeE fEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_mm dEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_mm SubtractionHistI FixedSizeStream fEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_S7_mm !dEEvNS0_4SpanINS_6detail20GradientPairInternalIT_EELm18446744073709551615EEES7_S7_mm ! fE !dE # 9BuildHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS3_9allocatorIS7_EEEENS0_16RowSetCollection4ElemERKNS0_16GHistIndexMatrixENS0_4SpanIS7_Lm18446744073709551615EEEb #1 $ 9BuildHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS3_9allocatorIS7_EEEENS0_16RowSetCollection4ElemERKNS0_16GHistIndexMatrixENS0_4SpanINS6_IdEELm18446744073709551615EEEb $1 'Ъ 4BuildBlockHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS3_9allocatorIS7_EEEENS0_16RowSetCollection4ElemERKNS0_21GHistIndexBlockMatrixENS0_4SpanIS7_Lm18446744073709551615EEE '6SubtractionTrickENS0_4SpanINS_6detail20GradientPairInternalIfEELm18446744073709551615EEES7_S7_ ) 4BuildBlockHistERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS3_9allocatorIS7_EEEENS0_16RowSetCollection4ElemERKNS0_21GHistIndexBlockMatrixENS0_4SpanINS6_IdEELm18446744073709551615EEE )6SubtractionTrickENS0_4SpanINS_6detail20GradientPairInternalIdEELm18446744073709551615EEES7_S7_ ) C *5BuildEPNS_7DMatrixEj * 2Ev *1Ev * 5BuildEPNS_7DMatrixEj +1 ,6ConcatERKNSt3__16vectorINS2_10unique_ptrIS1_NS2_14default_deleteIS1_EEEENS2_9allocatorIS7_EEEEj - 5BuildEPNS_7DMatrixEj ,4InitEPNSt3__16vectorINS0_15WQuantileSketchIffEENS2_9allocatorIS5_EEEEjm - г PNS_7DMatrixE ,RKNS_8MetaInfoE , 7SingleThreadBuildERKNS_10SparsePageERKNS_8MetaInfoEjbjjj -1LoadBalanceERKNS_10SparsePageEm - И 7GetValueFromUint8EPvm -8GetValueFromUint - 16EPvm .32EPvm . 2 .1 6engine 5 op7ReducerINS0_ /1SerializeReducerFunc_IN7xgboost6common22QuantileSketchTemplateIffNS2_ 12SerializeReduceClosureIN7xgboost6common22QuantileSketchTemplateIffNS2_ 3 3 /5BitORE SumE /M mEEvPKvPviRKN3MPI8DatatypeE 1dEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE
+ 9WQSummaryIffEEE16SummaryContainerEEEvPKvPviRKN3MPI8DatatypeE 310WXQSummaryIffEEE16SummaryContainerEEEvPKvPviRKN3MPI8DatatypeE ׆
+ 9WQSummaryIffEEE16SummaryContainerEE6InvokeEPv 310WXQSummaryIffEEE16SummaryContainerEE6InvokeEPv ݆
+ 6 50 ӄ5 1 7Learner 3 8ConsoleLoggerParam11__MANAGER__Ev 9PredictionContainer 4UnwoundPathSumEPKNS_11PathElementEjj HostDeviceVectorI 5GenericParameter fE 5NS_ ?iE HhE QyE ijE rmE z C 5D 7aSEOS1_ 71 :8HostSpanEv =4 =6 > 2E 61E 6 mfi 6St16initializer_listIfEi 7RKNSt3__16vectorIfNS2_9allocatorIfEEEEi 7OS1_ 7 mfi 7St16initializer_listIfEi 7RKNSt3__16vectorIfNS2_9allocatorIfEEEEi 7OS1_ 7Т Ч 2Ev 71Ev 7 7xgboost 85rabit6engine13AllreduceBase14ConnectTrackerEv 1 95Value7TypeStrEv 9JsonArrayeqERKNS_5ValueE 8 6common7Monitor ̡7 4 3gbm 6HostDeviceVectorI 90 č1 fE 9NS_ BiE KhE SyE ljE tmE | 5EmptyEv :4SizeEv :9 :1 ;8HostSpanEv = DeviceIdxEv :SetDeviceEi ?Я 0 :3DevicePointerEv <1HostPointerEv = DeviceSpanEv ;HostVectorEv = 5Const ;0 <8ConstDevicePointerEv <3 <6ConstHostPointerEv =1Host =2 ?4DeviceCanWriteEv ? DeviceSpanEv <HostVectorEv = DeviceSpanEv <HostVectorEv = а Device <ConstHostSpanEv = PointerEv =CanReadEv ? PointerEv =CanReadEv >в FillEf =CopyE = RK >St16initializer_listIfE > S1_ >NSt3__16vectorIfNS2_9allocatorIfEEEE > ExtendERKS1_ >ResizeEmf ? HostCanWriteEv ?DeviceAccessEv ? 6detail20GradientPairInternalIfEEE @11FeatureTypeEE Y5EntryEE a C @D BaSEOS4_ B1 C8HostSpanEv F4 G6 H 2E @1E A mS3_i ASt16initializer_listIS3_Ei BRKNSt3__16vectorIS3_NS5_9allocatorIS3_EEEEi BOS4_ B mS3_i BSt16initializer_listIS3_Ei BRKNSt3__16vectorIS3_NS5_9allocatorIS3_EEEEi BOS4_ B 2Ev B1Ev B 6detail20GradientPairInternalIfEEE C11FeatureTypeEE [5EntryEE d 5EmptyEv C4SizeEv C9 C1 D8HostSpanEv F DeviceIdxEv CSetDeviceEi H 0 D3DevicePointerEv E1HostPointerEv F DeviceSpanEv DHostVectorEv F 5Const E0 E8ConstDevicePointerEv E3 E6ConstHostPointerEv F1Host F2 H4DeviceCanWriteEv H DeviceSpanEv EHostVectorEv F DeviceSpanEv EHostVectorEv F Device FConstHostSpanEv F PointerEv FCanReadEv H PointerEv GCanReadEv H FillES3_ GCopyE G RK GSt16initializer_listIS3_E H S4_ GNSt3__16vectorIS3_NS5_9allocatorIS3_EEEE G ExtendERKS4_ HResizeEmS3_ H HostCanWriteEv HDeviceAccessEv H C ID KaSEOS1_ K1 L8HostSpanEv N4 O6 P 2E I1E J mii JSt16initializer_listIiEi JRKNSt3__16vectorIiNS2_9allocatorIiEEEEi JOS1_ K mii JSt16initializer_listIiEi JRKNSt3__16vectorIiNS2_9allocatorIiEEEEi JOS1_ K 2Ev K1Ev K 5EmptyEv K4SizeEv K9 K1 L8HostSpanEv N DeviceIdxEv LSetDeviceEi Q 0 L3DevicePointerEv N1HostPointerEv N DeviceSpanEv LHostVectorEv N 5Const M0 M8ConstDevicePointerEv N3 N6ConstHostPointerEv N1Host O2 P4DeviceCanWriteEv P DeviceSpanEv MHostVectorEv N DeviceSpanEv NHostVectorEv N Device NConstHostSpanEv N PointerEv NCanReadEv P PointerEv OCanReadEv P FillEi OCopyE O RK OSt16initializer_listIiE P S1_ PNSt3__16vectorIiNS2_9allocatorIiEEEE P ExtendERKS1_ PResizeEmi Q Ё HostCanWriteEv PDeviceAccessEv P C QD SaSEOS1_ S1 T8HostSpanEv V4 W6 X 2E Q1E R mhi RSt16initializer_listIhEi RRKNSt3__16vectorIhNS2_9allocatorIhEEEEi SOS1_ S mhi RSt16initializer_listIhEi SRKNSt3__16vectorIhNS2_9allocatorIhEEEEi SOS1_ S 2Ev S1Ev S 5EmptyEv S4SizeEv S9 S1 T8HostSpanEv V DeviceIdxEv TSetDeviceEi Y 0 T3DevicePointerEv V1HostPointerEv V DeviceSpanEv THostVectorEv VА 5Const U0 U8ConstDevicePointerEv V3 V6ConstHostPointerEv W1Host W2 X4DeviceCanWriteEv Y DeviceSpanEv UHostVectorEv W DeviceSpanEv VHostVectorEv V Device VConstHostSpanEv W PointerEv VCanReadEv YБ В PointerEv WCanReadEv X FillEh WCopyE W RK WSt16initializer_listIhE X S1_ XNSt3__16vectorIhNS2_9allocatorIhEEEE XГ ExtendERKS1_ XResizeEmh Y HostCanWriteEv XDeviceAccessEv YС C YD [aSEOS2_ [1 \8HostSpanEv _4 _6 ` 2E Y1E Z mS1_i ZSt16initializer_listIS1_Ei [RKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi [OS2_ [ mS1_i [St16initializer_listIS1_Ei [RKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi [OS2_ [ 2Ev [1Ev [Ъ Ы 5EmptyEv \4SizeEv \9 \1 ]8HostSpanEv _ Ю DeviceIdxEv \SetDeviceEi a 0 \3DevicePointerEv ^1HostPointerEv _ DeviceSpanEv ]HostVectorEv _ 5Const ]0 ^8ConstDevicePointerEv ^3 ^6ConstHostPointerEv _1Host _2 a4DeviceCanWriteEv a DeviceSpanEv ^HostVectorEv _ DeviceSpanEv ^HostVectorEv _ Я Device ^ConstHostSpanEv _ PointerEv ^CanReadEv a PointerEv _CanReadEv ` FillES1_ _CopyE _ RK `St16initializer_listIS1_E ` S2_ `NSt3__16vectorIS1_NS3_9allocatorIS1_EEEE ` ExtendERKS2_ `ResizeEmS1_ aл о HostCanWriteEv aDeviceAccessEv a C aD caSEOS2_ d1 d8HostSpanEv g4 g6 i 2E b1E b mS1_i bSt16initializer_listIS1_Ei cRKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi cOS2_ c mS1_i cSt16initializer_listIS1_Ei cRKNSt3__16vectorIS1_NS3_9allocatorIS1_EEEEi cOS2_ c 2Ev c1Ev c 5EmptyEv d4SizeEv d9 d1 e8HostSpanEv g DeviceIdxEv dSetDeviceEi i 0 e3DevicePointerEv f1HostPointerEv g DeviceSpanEv eHostVectorEv g 5Const f0 f8ConstDevicePointerEv f3 f6ConstHostPointerEv g1Host g2 i4DeviceCanWriteEv i DeviceSpanEv fHostVectorEv g DeviceSpanEv fHostVectorEv g Device gConstHostSpanEv g PointerEv gCanReadEv i PointerEv gCanReadEv i FillES1_ hCopyE h RK hSt16initializer_listIS1_E h S2_ hNSt3__16vectorIS1_NS3_9allocatorIS1_EEEE h ExtendERKS2_ iResizeEmS1_ i HostCanWriteEv iDeviceAccessEv i C jD kaSEOS1_ l1 m8HostSpanEv o4 p6 q 2E j1E k myi kSt16initializer_listIyEi kRKNSt3__16vectorIyNS2_9allocatorIyEEEEi kOS1_ l myi kSt16initializer_listIyEi kRKNSt3__16vectorIyNS2_9allocatorIyEEEEi kOS1_ l 2Ev l1Ev l 5EmptyEv l4SizeEv l9 l1 m8HostSpanEv o DeviceIdxEv lSetDeviceEi q 0 m3DevicePointerEv o1HostPointerEv o DeviceSpanEv mHostVectorEv o 5Const n0 n8ConstDevicePointerEv o3 o6ConstHostPointerEv o1Host o2 q4DeviceCanWriteEv q DeviceSpanEv nHostVectorEv o DeviceSpanEv nHostVectorEv o Device oConstHostSpanEv o PointerEv oCanReadEv q PointerEv pCanReadEv q FillEy pCopyE p RK pSt16initializer_listIyE q S1_ qNSt3__16vectorIyNS2_9allocatorIyEEEE q
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DeviceSpanEv wHostVectorEv wИ
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C zD |aSEOS1_ |1 }8HostSpanEv 4 ʀ6 ˁ 2E z1E { mmi {St16initializer_listImEi |RKNSt3__16vectorImNS2_9allocatorImEEEEi |OS1_ |
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4ReadEPvm 8PeekReadEPvm
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ReadEPvm SeekEm TakeEPNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE DŽ
Json SparsePage ExtendPathEPNS_11PathElementEjffi UnwindPathEPNS_11PathElementEjj Writer Object String Number œReader 4SaveENS_4JsonE 5VisitEPKNS_ 9JsonArrayE 1 8JsonNullE 0Json І1Json ObjectE NumberE StringE IntegerE BooleanE DummyJsonObjectEv LoadFeatureTypeERKNSt3__16vectorINS0_12basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEENS5_IS7_EEEEPNS1_INS_11FeatureTypeENS5_ISC_EEEE GradientBooster6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterEPKNS_17LearnerModelParamE C ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE 2EO 1EO ϋ S0_ ɋNSt3__13mapINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEENS_4JsonENS1_4lessIS8_EENS6_INS1_4pairIKS8_S9_EEEEEE ߌ S0_ ٌNSt3__13mapINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEENS_4JsonENS1_4lessIS8_EENS6_INS1_4pairIKS8_S9_EEEEEE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i Json SparsePage12GetTransposeEi ߷ ObjecteqERKNS_5ValueE StringeqERKNS_5ValueE NumbereqERKNS_5ValueE ՔReader5ErrorENSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE ixE ӏaSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i Љ JsonArray GPUMetric15CreateGPUMetricERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE predictor Predictor TreeParam11__MANAGER__Ev C ixE ڒaSERKNS_5ValueE 4SaveEPNS_10JsonWriterE 2EOS0_ Β1EOS0_ Ԓ RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i О б ixE aSERKNS_5ValueE ۔4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE ɔi ϔ Json EllpackPage ջObjFunction6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE TreeUpdater6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE LearnerImpl14kRandSeedMagicE Integer Boolean ƛ ixE їaSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i Json ʘEllpackPage4SizeEv IntegereqERKNS_5ValueE BooleaneqERKNS_5ValueE ֜ JsonNull ParseStrERKNSt3__112basic_stringIcNS0_11char_traitsIcEENS0_9allocatorIcEEEE MetaInfo ixE aSERKNS_5ValueE 4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE i JsonNulleqERKNS_5ValueE MetaInfo ixE aSERKNS_5ValueE ܜ4SaveEPNS_10JsonWriterE RKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE ʜi М І 5ParseEv 1 4LoadEv 9ParseNullEv В 0 ӝ1Parse 2ParseBooleanEv ў3kMaxNumLengthE SkipSpacesEv ParseArrayEv StringEv ObjectEv ŞNumberEv ˞ Ю Json data tree 4 aSERKS0_ LoadE ܟDumpES0_PNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEE NS_10StringViewE PNS_10JsonReaderE 5StartERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 4StopERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE ơ 21CollectFromOtherRanksEv 15PrintStatisticsERKNSt3__13mapINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEENS2_4pairImmEENS2_4lessIS9_EENS7_INSA_IKS9_SB_EEEEEE 5PrintEv axE inE mEEvPKvPviRKN3MPI8DatatypeE ǥyEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE Н Version DMatrix Learner RegTree 4 6StringERKNSt3__15tupleIJiiiEEE ާ8kInvalidE LoadE æS RKNS_4JsonEb PN4dmlc6StreamE a elfEv ҧ veEPN meERKNSt3__15tupleIJiiiEEE S_4JsonE ̧4dmlc6StreamE ا 7xgboost S_16ParserFactoryRegI 4 1 9MetricRegEE3GetEv data19SparsePageFormatRegINS1_ tree17SplitEvaluatorRegEE3GetEv 1 7CSCPageEEEE3GetEv 0SparsePageEEEE3GetEv 3SortedCSCPageEEEE3GetEv 1EllpackPageEEEE3GetEv 6CreateI D 4LoadERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEbbS9_m ٷ PvS2_FvS2_EFiS2_EEEPS0_T_T0_PT1_PT2_fii NS_4data1 2DenseAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm ܮ0CS 6DataTableAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 1FileAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 5IteratorAdapterIPvFiS4_PFiS4_15XGBoostBatchCSRES4_ES5_EEEEPS0_PT_fiRKNSt3__112basic_stringIcNSD_11char_traitsIcEENSD_9allocatorIcEEEEm RAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm CAdapterEEEPS0_PT_fiRKNSt3__112basic_stringIcNS7_11char_traitsIcEENS7_9allocatorIcEEEEm 4Push հ7PushCSCERKS0_ INS_4data ERKS0_ 1 21DataTableAdapterBatchEEEyRKT_fi 7DenseAdapterBatchEEEyRKT_fi 5CS 6FileAdapterBatchEEEyRKT_fi RAdapterBatchEEEyRKT_fi CAdapterBatchEEEyRKT_fi Ъ 5ClearEv 1 7SetInfoEPKc 6ExtendERKS0_b ̶9kNumFieldE 1 5SliceENS_6common4SpanIKiLm18446744073709551615EEE ѵ7GetInfoEPKcPyNS_8DataTypeEPPKv 8ValidateEi Ҷ 0SaveBinaryEPN4dmlc6StreamE 4GetFeatureInfoEPKcPNSt3__16vectorINS3_12basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEENS8_ISA_EEEE ƶ 0LoadBinaryEPN4dmlc6StreamE ˵4SetFeatureInfoEPKcPS2_y PKvNS_8DataTypeEm RKNSt3__112basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEE ض DMatrix14GetThreadLocalEv Learner19AllowLazyCheckPointEv RegTree к 2Ev Ƿ1Ev ͷ0Ev ӷ 7xgboost4data16SparsePageWriterINS7_10SparsePageEEC1ERKNS_6vectorINS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEENSG_ISI_EEEESM_mEUlvE_EEEEEPvSP_ 4dmlc 12ThreadedIterIN ع4data14TextParserBaseI 7xgboost S 1 7CSCPageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ 0SparsePageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ ϻ3SortedCSCPageEE4InitENS_8functionIFbPPSA_EEENSC_IFvvEEEEUlvE_EEEEEPvSL_ C D 12SetBaseRowIdEm 2E 1E v PNS_7DMatrixERKNS_10BatchParamE v ݼPNS_7DMatrixERKNS_10BatchParamE 2Ev 1Ev 1 49__dmlc_registry_file_tag_sparse_page_raw_format__Ev 7 3SimpleDMatrix EllpackPageSourceC SparsePageDMatrix 2EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE 1EPNS_7DMatrixERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEERKNS_10BatchParamE C 4InfoEv 5SliceENS_6common4SpanIKiLm18446744073709551615EEE 1 22GetSortedColumnBatchesEv 2 1 INS0_1 EPN4dmlc6StreamE 2DenseAdapterEEEPT_fi 0CS 6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi 5IteratorAdapterIPvFiS4_PFiS4_15XGBoostBatchCSRES4_ES5_EEEEPT_fi INS0_1 EPN4dmlc6StreamE 2DenseAdapterEEEPT_fi 0CS 6DataTableAdapterEEEPT_fi 1FileAdapterEEEPT_fi 5IteratorAdapterIPvFiS4_PFiS4_15XGBoostBatchCSRES4_ES5_EEEEPT_fi RAdapterEEEPT_fi CAdapterEEEPT_fi RAdapterEEEPT_fi CAdapterEEEPT_fi data1 tree1 3SimpleDMatrix4InfoEv 7SparsePageDMatrix4InfoEv 3GetRowBatchesEv 6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE 5SaveToLocalFileERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE Љ Ќ 4InfoEv 1 22GetSortedColumnBatchesEv 3GetRowBatchesEv 6GetColumnBatchesEv 7GetEllpackBatchesERKNS_10BatchParamE ! ! gbm obj 2FeatureInteractionConstraintHost 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 6GBTree 4DartTrainParam11__MANAGER__Ev 1GBTreeModel " 1 6GBTree 3GBLinearModel9SaveModelEPNS_4JsonE 1GBTreeModel З% % % 8GradientBoosterRegEE3GetEv 6LinearUpdaterRegEE3GetEv 2 4 0TreeGenRegEE3GetEv % % % 9 1 2 7DoBoostEPNS_7DMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_20PredictionCacheEntryE ConfigureERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE LoadModelERKNS_4JsonE % 7ConfigureUpdatersEv 1 3BoostNewTreesEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEiPNSt3__16vectorINSA_10unique_ptrINS_7RegTreeENSA_14default_deleteISD_EEEENSA_9allocatorISG_EEEE 0LoadConfigERKNS_4JsonE 2PredictBatchEPNS_7DMatrixEPNS_20PredictionCacheEntryEbj % InitUpdaterERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE CommitModelEONSt3__16vectorINS3_INS2_10unique_ptrINS_7RegTreeENS2_14default_deleteIS5_EEEENS2_9allocatorIS8_EEEENS9_ISB_EEEEPNS_7DMatrixEPNS_20PredictionCacheEntryE % 2ConfigureWithKnownDataERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEEPNS_7DMatrixE 6PerformTreeMethodHeuristicEPNS_7DMatrixE % % % & & & hn S I VN 8_N 16_N7xgboost7LearnerD 7xgboost K7xgboost3gbm6GBTree10SaveConfigEPNS_4JsonE 3gbm6GBTree10LoadConfigERKNS_4JsonE 7LearnerD & 1 9SaveModelEPNS_4JsonE 0SaveConfigEPNS_4JsonE 2GetPredictorEPKNS_16HostDeviceVectorIfEEPNS_7DMatrixE & & & & & & ModelParam11__MANAGER__Ev TrainParam11__MANAGER__Ev & ' ' 4SaveEPN4dmlc6StreamE 9SaveModelEPNS_4JsonE * 4LoadEPN4dmlc6StreamE 9LoadModelERKNS_4JsonE * * * * D 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1__make_MetricReg_ 3__make_MetricReg_TweedieNLogLik__E 7 8 9 3 41__dmlc_registry_file_tag_ 22 1 9ListEntry7CmpPredERKS1_S3_ 4__dmlc_registry_file_tag_aft_obj__Ev 6__dmlc_registry_file_tag_hinge_obj__Ev 5__dmlc_registry_file_tag_rank_obj__Ev ; < multiclass_obj__Ev regression_obj__Ev < SoftmaxMultiClassParam11__MANAGER__Ev PoissonRegressionParam11__MANAGER__Ev TweedieRegressionParam11__MANAGER__Ev < ObjFunctionRegEE3GetEv TreeUpdaterRegEE3GetEv = = = 5LambdaRankParam11__MANAGER__Ev 2RegLossParam11__MANAGER__Ev = > @ @ @ Б@ 40__dmlc_registry_file_tag_cpu_predictor__Ev 9PredValueERKNS_6common4SpanIKNS_5EntryELm18446744073709551615EEERKNSt3__16vectorINS8_10unique_ptrINS_7RegTreeENS8_14default_deleteISB_EEEENS8_9allocatorISE_EEEERKNS9_IiNSF_IiEEEEiPNSB_4FVecEjj D D зF 19ClearExpiredEntriesEv 5 9ContainerEv F CacheENSt3__110shared_ptrINS_7DMatrixEEEi EntryEPNS_7DMatrixE F F F 9ConfigureERKNSt3__16vectorINS1_4pairINS1_12basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEES9_EENS7_ISA_EEEE 6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEEPKNS_16GenericParameterE F F 9 5ResetEv ConfigureERKNS_4tree10TrainParamEj SplitImplEijii F F F G G G 1 4 22CPUHistMakerTrainParam11__MANAGER__Ev 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 G G G G 4SplitEvaluator17ComputeSplitScoreEjjRKNS0_9GradStatsES4_ 7QuantileHistMaker7BuilderI G H H H 6CreateERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS_10FeatureMapEb 5MatchERKNSt3__112basic_stringIcNS1_11char_traitsIcEENS1_9allocatorIcEEEERKNS1_3mapIS7_S7_NS1_4lessIS7_EENS5_INS1_4pairIS8_S7_EEEEEE H H 9 5EqualERKS0_ 1 4SaveEPN4dmlc6StreamE ŀ2 8TreeShapERKNS0_4FVecEPfjjPNS_11PathElementEffiijf DumpModelERKNS_10FeatureMapEbNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE SaveModelEPNS_4JsonE р лH H 2GetNumLeavesEv 6GetNumSplitNodesEv H H 4LoadEPN4dmlc6StreamE 9LoadModelERKNS_4JsonE ˀ1 ׀5kRootE H H H I 8FillNodeMeanValuesEv 7FillNodeMeanValueEi J J 8CalculateContributionsApproxERKNS0_4FVecEPf 2CalculateContributionsERKNS0_4FVecEPfij ЂJ J J J МJ J M P P 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_ P P S 2ReducerSafe_IN7xgboost ф3 4tree 6detail20GradientPairInternalIdEEXadL_ZNS4_6ReduceERS4_RKS4_EEEEvPKvPviRKN3MPI8DatatypeE 9GradStatsEXadL_ZNS3_6ReduceERS3_RKS3_EEEEvPKvPviRKN3MPI8DatatypeE ц11SketchMaker7SKStatsEXadL_ZNS4_6ReduceERS4_RKS4_EEEEvPKvPviRKN3MPI8DatatypeE T T U U InvokeLambda_EPv ReducerAlign_IN7xgboost6detail20GradientPairInternalIfEEXadL_ZNS4_6ReduceERS4_RKS4_EEEEvPKvPviRKN3MPI8DatatypeE V ЊW 7BuilderI ӊ9ConfigureERKNSt3__16vectorINS2_4pairINS2_12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEESA_EENS8_ISB_EEEE 6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEE 21UpdatePredictionCacheEPKNS_7DMatrixEPNS_16HostDeviceVectorIfEE fE dE C 6UpdateERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEPNS_7RegTreeE 8InitDataERKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 1 9 2 2ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS8_INS0_14SplitEvaluatorENSA_ISD_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE 1ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS8_INS0_14SplitEvaluatorENSA_ISD_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE W W W W 9 6S 1 2InitSamplingERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEERKNS_7DMatrixEPNS5_ImNS9_ImEEEE 4 0ApplySplitENSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSA_12ColumnMatrixERKNSA_14HistCollectionIfEEPNS_7RegTreeE ٦7AddSplitsToRowSetERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPNS_7RegTreeE 3SplitSiblingsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPS9_SC_PNS_7RegTreeE 5 ExpandWith SetHistSynchronizerEPNS0_16HistSynchronizerIfEE ڡFindSplitConditionsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_7RegTreeERKNS_6common16GHistIndexMatrixEPNS5_IiNS7_IiEEEE ߦ 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0BuildLocalHistogramsERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSD_9allocatorISH_EEEE 2EvaluateAndApplySplitsERKNS_6common16GHistIndexMatrixERKNS4_12ColumnMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSF_9allocatorISH_EEEE 4BuildHistogramsLossGuideENS3_11ExpandEntryERKNS_6common16GHistIndexMatrixERKNS5_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSE_9allocatorISI_EEEE X ЎX X ExpandEntryC InitNewNodeEiRKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 2Eiiifj 1Eiiifj X ЏX fE11ExpandEntry7IsValidERKNS0_10TrainParamEi dE11ExpandEntry7IsValidERKNS0_10TrainParamEi X АX X EvaluateSplitsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSC_14HistCollectionIfEERKNS_7RegTreeE ӦBuildNodeStatsERKNS_6common16GHistIndexMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSC_9allocatorISG_EEEE X кX X X X X X X Y Y Y AddSplitsToTreeERKNS_6common16GHistIndexMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSC_9allocatorISE_EEEESI_ PartitionKernelI Y C 6UpdateERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixEPNS_7RegTreeE 8InitDataERKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 1 9 2 2ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS8_INS0_14SplitEvaluatorENSA_ISD_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE 1ERKNS0_10TrainParamENSt3__110unique_ptrINS_11TreeUpdaterENS7_14default_deleteIS9_EEEENS8_INS0_14SplitEvaluatorENSA_ISD_EEEENS_32FeatureInteractionConstraintHostEPKNS_7DMatrixE Y Y Y Y 9 6S 1 2InitSamplingERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS4_9allocatorIS8_EEEERKNS_7DMatrixEPNS5_ImNS9_ImEEEE 4 0ApplySplitENSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSA_12ColumnMatrixERKNSA_14HistCollectionIdEEPNS_7RegTreeE 7AddSplitsToRowSetERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPNS_7RegTreeE 3SplitSiblingsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEEPS9_SC_PNS_7RegTreeE 5 ExpandWith ۳SetHistSynchronizerEPNS0_16HistSynchronizerIdEE FindSplitConditionsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_7RegTreeERKNS_6common16GHistIndexMatrixEPNS5_IiNS7_IiEEEE LossGuideERKNS_6common16GHistIndexMatrixERKNS4_21GHistIndexBlockMatrixERKNS4_12ColumnMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSI_9allocatorISM_EEEE 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2EvaluateAndApplySplitsERKNS_6common16GHistIndexMatrixERKNS4_12ColumnMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSF_9allocatorISH_EEEE 4BuildHistogramsLossGuideENS3_11ExpandEntryERKNS_6common16GHistIndexMatrixERKNS5_21GHistIndexBlockMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSE_9allocatorISI_EEEE Y Z Z ExpandEntryC InitNewNodeEiRKNS_6common16GHistIndexMatrixERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENS8_9allocatorISC_EEEERKNS_7DMatrixERKNS_7RegTreeE 2Eiiifj 1Eiiifj ЄZ Z Z Z Z EvaluateSplitsERKNSt3__16vectorINS3_11ExpandEntryENS4_9allocatorIS6_EEEERKNS_6common16GHistIndexMatrixERKNSC_14HistCollectionIdEERKNS_7RegTreeE BuildNodeStatsERKNS_6common16GHistIndexMatrixEPNS_7DMatrixEPNS_7RegTreeERKNSt3__16vectorINS_6detail20GradientPairInternalIfEENSC_9allocatorISG_EEEE Z Z Z Z Z Z Z Z Z Z Z AddSplitsToTreeERKNS_6common16GHistIndexMatrixEPNS_7RegTreeEPiiPjPNSt3__16vectorINS3_11ExpandEntryENSC_9allocatorISE_EEEESI_ PartitionKernelI Z hEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE tEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE jEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE [ [ [ hEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE tEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE jEEvmmNS_6common7Range1dEiRKNS5_12ColumnMatrixERKNS_7RegTreeE [ [ [ [ [ [ [ \ ^ _ refresh__Ev skmaker__Ev ` ` ` a 1 4InitEiPPc 8FinalizeEv 9 3AllreduceBase 5AllreduceRobust 2 1DataRequestERKNSt3__14pairIbiEERKNS1_6vectorIcNS1_9allocatorIcEEEEm 0Allreduce_EPvmmPFvPKvS1_iRKN3MPI8DatatypeEENS0_3mpi8DataTypeENSA_6OpTypeEPFvS1_ES1_PKciSG_ C 4InitEiPPc 1 8S 20TryReduceScatterRingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE 2Ev 1Ev b b b 4ReConnectLinksEPKc 2Tr 6TryAll Лb hutdownEv etParamEPKcS3_ b b ackerPrintERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE y b b AllreduceEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE BroadcastEPvmi b reduce gatherRingEPvmmmm RingEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE TreeEPvmmPFvPKvS2_iRKN3MPI8DatatypeEE c c c c c C 4InitEiPPc 8S 1 9 20Try 2Ev 1Ev c utils c_api9All 5ErrorEPKcz 6AssertEbPKcz 21STOP_PROCESS_ON_ERRORE d d d d hutdownEv etParamEPKcS3_ d 1 7 5 4 3 6TryDecideRoutingENS1_11RecoverTypeEPmPiPNSt3__16vectorIbNS5_9allocatorIbEEEE 2TryGetResultEPvmib R CheckPoint_EPKN4dmlc12SerializableES5_b ecoverExecEPvmiiiPKc ingPassingEPvmmmmPNS0_13AllreduceBase10LinkRecordES5_ d d SetBootstrapCacheERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEPKvmm GetBootstrapCacheERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEPvmm TryLoadCheckPointEb d d All BroadcastEPvmiPKciS4_ gatherEPvmmmmPKciS4_ reduceEPvmmPFvPKvS2_iRKN3MPI8DatatypeEEPFvS2_ES2_PKciSE_ d CheckAndRecoverENS0_13AllreduceBase10ReturnTypeE LocalModelCheckEb TryRestoreCacheEbii d d d LoadCheckPointEPN4dmlc12SerializableES4_ TryRecoverDataENS1_11RecoverTypeEPvmiRKNSt3__16vectorIbNS4_9allocatorIbEEEE e e e CheckinLocalStateEPNSt3__16vectorImNS2_9allocatorImEEEEPNS2_12basic_stringIcNS2_11char_traitsIcEENS4_IcEEEE RecoverLocalStateEPNSt3__16vectorImNS2_9allocatorImEEEEPNS2_12basic_stringIcNS2_11char_traitsIcEENS4_IcEEEE e TryResetLinksEv ActionSummary7ReducerEPKvPviRKN3MPI8DatatypeE e e ShortestDistERKNSt3__14pairIbmEERKNS1_6vectorINS2_IimEENS1_9allocatorIS7_EEEEm ReduceHandle e f f f f f f f f g g GetEngineEv AllgatherEPvmmmmPKciS3_ Йg g g C D 8TypeSizeERKN3MPI8DatatypeE 4InitEPFvPKvPviRKN3MPI8DatatypeEEm 9AllreduceEPvmmPFvS2_ES2_PKciS6_ 2Ev 1Ev g g 2Ev 1Ev g g g g g reduceEPvmNS_6engine3mpi8DataTypeENS3_6OpTypeEPFvS1_ES1_ gatherEPvmmmmi Хg g I Finalize Get TrackerPrint Broadcast All L CheckPoint VersionNumber nit sDistributed g g R WorldSize ProcessorName ingPrevRank ank дg g g g еg g g gather reduce g йg oadCheckPoint inkTag g пg g g g g g g g cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE fEEvPKvPviRKN3MPI8DatatypeE dEEvPKvPviRKN3MPI8DatatypeE g g g g g g g g g g g g g cEEvPKvPviRKN3MPI8DatatypeE hEEvPKvPviRKN3MPI8DatatypeE iEEvPKvPviRKN3MPI8DatatypeE jEEvPKvPviRKN3MPI8DatatypeE lEEvPKvPviRKN3MPI8DatatypeE mEEvPKvPviRKN3MPI8DatatypeE Ђh h h h h h 7 6LibFMParserParam11__MANAGER__Ev 4CSVParserParam11__MANAGER__Ev 8CreateLibSVMParserI 5CreateCSVParserI LibSVMParserParam11__MANAGER__Ev CreateLibFMParserI h h h RowBlockIterI ThreadedIterINS_2io14InputSplitBase5ChunkEE14NotImplementedEv ̆ j y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ h fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ h h h h h ParserI Stream6CreateEPKcS2_b j y fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ йh fE6CreateEPKcjjS3_ iE6CreateEPKcjjS3_ xE6CreateEPKcjjS3_ h h h h i j y fEEE3GetEv iEEE3GetEv xEEE3GetEv i i i fEEE3GetEv iEEE3GetEv xEEE3GetEv i i i 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 Цi i 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 i i 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 i 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 i i i i i 7_ _6vectorINS7_4data17RowBlockContainerI 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ Ɔ j y fEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ iEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ xEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ j fEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ iEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ xEEE4InitENS_8functionIFbPPSB_EEENSD_IFvvEEEEUlvE_EEEEEPvSM_ k Ўm n зo p j y fE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjfEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ iE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjiEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ xE8FillDataEPNS_6vectorINS8_17RowBlockContainerIjxEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ Ńq jfEENS_9allocatorISC_EEEEE4InitENS_8functionIFbPPSF_EEENSH_IFvvEEEEUlvE_EEEEEPvSQ_ yfEENS_9allocatorISC_EEEEE4InitENS_8functionIFbPPSF_EEENSH_IFvvEEEEUlvE_EEEEEPvSQ_ r fE8FillDataEPNS_6vectorINS8_17RowBlockContainerIyfEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ iE8FillDataEPNS_6vectorINS8_17RowBlockContainerIyiEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ xE8FillDataEPNS_6vectorINS8_17RowBlockContainerIyxEENS_9allocatorISD_EEEEEUlvE_EEEEEPvSK_ ˃s s u v v w 1 23IndexedRecordIOSplitter 0FileSystem Մ2LineSplitter1 ҆6RecordIOSplitter1 4InputSplitBase 5LocalFileSystem Ց 11GetInstanceERKNS0_3URIE Ѕ22ListDirectoryRecursiveERKNS0_3URIEPNSt3__16vectorINS0_8FileInfoENS5_9allocatorIS7_EEEE ɑ w InputSplit6CreateEPKc SeekStream13CreateForReadEPKcb jjS2_ S2_jjS2_bimb w w w w x y 5SeekRecordBeginEPNS_6StreamE ݇9FindLastRecordBeginEPKcS3_ 7ExtractNextRecordEPNS_10InputSplit4BlobEPNS0_14InputSplitBase5ChunkE Уy y y 5SeekRecordBeginEPNS_6StreamE 9FindLastRecordBeginEPKcS3_ 7ExtractNextRecordEPNS_10InputSplit4BlobEPNS0_14InputSplitBase5ChunkE y Ыy y 1 9 Ë 4ResetPartitionEjj 3ReadIndexFileEPNS0_10FileSystemERKNSt3__112basic_stringIcNS4_11char_traitsIcEENS4_9allocatorIcEEEE 5SeekRecordBeginEPNS_6StreamE 9FindLastRecordBeginEPKcS3_ 7ExtractNextRecordEPNS_10InputSplit4BlobEPNS0_14InputSplitBase5ChunkE 1 y y y y y ReadChunkEPvPm ߋNext y ChunkEPNS_10InputSplit4BlobE BatchEPNS_10InputSplit4BlobEm y NextBatchExEPNS0_14InputSplitBase5ChunkEm BeforeFirstEv y y y 4 1 D Ԑ8StripEndENSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEc 9ReadChunkEPvPm 5Chunk InitEPNS0_10FileSystemEPKcmb ReadEPvm y 7InitInputFileInfoERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEb 4ResetPartitionEjj Ȑ1BeforeFirstEv ΐ3ConvertToURIsERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEE 6ExtractNextChunkEPNS_10InputSplit4BlobEPNS1_5ChunkE Ñ y z z 2Ev 1Ev 0Ev z z z Зz z z z 4LoadEPS1_m 6AppendEPS1_m z z z } } 1 4OpenERKNS0_3URIEPKcb 1 Β3ListDirectoryERKNS0_3URIEPNSt3__16vectorINS0_8FileInfoENS5_9allocatorIS7_EEEE GetPathInfoERKNS0_3URIE OpenForReadERKNS0_3URIEb ~ ~ ~ ~ N ZN PF F 7xgboost St3__1 ˖4dmlc 5rabit 4 6 1 9 8JsonNullE ۰5 ϸ7 3 20LearnerConfigurationE data tree 1 6detail19SingleBatchDataIterINS0_ š2 5IteratorAdapterIPvFiS2_PFiS2_15XGBoostBatchCSRES2_ES3_EE 2D 0CS 6 1FileAdapterE 3SimpleDMatrixE 7SparsePageDMatrixE 9SparsePageRawFormatINS_ MatrixProxyE ĖenseAdapterE ٥ 2 ޖ1 6__ 0__ 3__match_any_but_newlineIcEE ՠ8__begin_marked_subexpressionIcEE 6__end_marked_subexpressionIcEE 1__empty_non_own_stateIcEE â shared_ptr_ ܘmatch_char_collateIcNS_12regex_traitsIcEEEE bracket_expressionIcNS_12regex_traitsIcEEEE pointerIPN emplaceIN7xgboost16HostDeviceVectorIjEENS_9allocatorIS3_EEEE 7xgboost S_13__empty_stateIcEENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 1 ƛ7DMatrixENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 4data1 8JsonNullENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 9JsonArrayENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 7BatchIteratorImplINS1_ 0 Ͳ1Json 1 7CSCPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE ج 0SparsePageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE 3SortedCSCPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE 1EllpackPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE
+4 О0 Ψ3 9basic_ 5 7 8 1__ 6__ 2__match_charIcEE ơ default_deleteIN basic_ifstreamIcNS_11char_traitsIcEEEE ܭ 7xgboost S_13__empty_stateIcEEEE 1 7DMatrixEEE 4data1 8JsonNullEEE 9JsonArrayEEE 7BatchIteratorImplINS1_ 0 ȴ1Json 1 7CSCPageEEEEE ߬ 0SparsePageEEEEE 3SortedCSCPageEEEEE 1EllpackPageEEEEE RAdapterE CAdapterE Фڪ 1 21DataTableAdapterBatchEEE 5CS 7DenseAdapterBatchEEE RAdapterBatchEEE CAdapterBatchEEE פ 8DataIterIN 1 6 9parameter1 ö5ErrorE 7istream ʹ4data 2io ɖ 7xgboost S 4data 1 7CSCPageEEE 1 21DataTableAdapterBatchEEE 5CS 7DenseAdapterBatchEEE 6FileAdapterBatchEEE ù RAdapterBatchEEE ɤCAdapterBatchEEE ޤ ͬ 䭈 DataTableAdapterE SparsePageFormatINS_ 5 Х6engine utils1 c_api1 8MemoryBufferStreamE 9MemoryFixSizeBufferE ᯈ 2D 0CSRAdapterENS_14default_deleteIS3_EENS_9allocatorIS3_EEEE MatrixProxyENS_14default_deleteIS3_EENS_9allocatorIS3_EEEE enseAdapterENS_14default_deleteIS3_EENS_9allocatorIS3_EEEE 2D 0CSRAdapterEEE MatrixProxyEEE enseAdapterEEE Ǩٱ shared_ptrIN7xgboost4data1 __ 2DenseAdapterEEE 0CSRAdapterEEE 賈 Ѵ 8kFloatPow5InvSplitE 5kFloatPow5SplitE common linear metric MetricE 1 ɪ9DenseCutsE ͫ6ColumnI 0SparseCutsE 1 2SparseColumnI 6PeekableInStreamE έ5FixedSizeStreamE խ CutsBuilderE ƫDenseColumnI ԫ hEE tEE jEE ì hEE tEE jEE ʬ hEE tEE jEE Ѭ È Ĉ Ĉ 0 2 ۼ SeekStreamE ParamErrorE InputSplitE Ĉ StreamE ǭParserI ň ň ň ň basic_filebufIcNS_11char_traitsIcEEEE __ ƈ ƈ 0Json 1 7 5GradientBoosterE 2ConfigurableE 3 StringE ObjectE NumberE ReaderE WriterE ƈ JsonArrayE LearnerIOE predictor12CPUPredictorE PredictorE Lj Lj Lj Json LearnerImplE ObjFunctionE TreeUpdaterE IntegerE BooleanE Lj Lj Lj Ȉ Ȉ Ȉ Ɉ istringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE ostringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE ȸɈ basic_stringbufIcNS_11char_traitsIcEENS_9allocatorIcEEEE Ʋ__ ʈ Json SparsePageENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE ObjectENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE NumberENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE StringENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE ʈ Json SparsePageEEE ObjectEEE NumberEEE StringEEE ˈ ˈ ̈ IntegerENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE BooleanENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE ͈ BooleanEEE IntegerEEE ͈ 0FieldEntryI 7FieldEntryNumericINS0_10FieldEntryI 4FieldEntryBaseINS0_10FieldEntryI 6FieldAccessEntryE N mEE bEE fEE jEE iEE xEE dEE 7xgboost St3__1 6common27ProbabilityDistributionTypeEEE 1 Έ Ј Ј ValueE ModelE Ј Ј ш ҈ Ԉ Ԉ DMatrixE LearnerE RegTreeE Ԉ Ԉ Ԉ E ܹ5InBufE Ո Ո iEEiEE xEExEE mEEmEE fEEfEE dEEdEE jEEjEE Ո iEEiEE NSt3__1 bEEbEE xEExEE mEEmEE fEEfEE dEEdEE jEEjEE Ո bad_function_callE __ ֈ ֈ 4ExternalMemoryPrefetcherINS_ 3S 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 0SparsePageEEE Լ3SortedCSCPageEEE ؈ ThreadedIterIN S RowBlockIterI 7xgboost S 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE ؈ copedThreadE erializableE ؈ function6__ Ⱦl_anchorIcEE r_anchorIcEE back_refIcEE ۡ funcI ݾbaseIF ZN PF 7xgboost4 4dmlc data24ExternalMemoryPrefetcherINS2_ tree1 1 7CSCPageEEC1ERKNS3_9CacheInfoEEUl 0SparsePageEEC1ERKNS3_9CacheInfoEEUl 3SortedCSCPageEEC1ERKNS3_9CacheInfoEEUl PPS5_E_NS_9allocatorISC_EEFbSB_EEE vE_NS_9allocatorISA_EEFvvEEE ؈ b vvEEE PN7xgboost PPN N7xgboost4tree17QuantileHistMaker7BuilderI 7xgboost 4dmlc S_6vectorIN4dmlc4data17RowBlockContainerI 1 7CSCPageEEEE 0SparsePageEEEE 3SortedCSCPageEEEE ڈ 7xgboost4 4dmlc data24ExternalMemoryPrefetcherINS_ tree1 1 7CSCPageEEC1ERKNS0_9CacheInfoEEUl 0SparsePageEEC1ERKNS0_9CacheInfoEEUl 3SortedCSCPageEEC1ERKNS0_9CacheInfoEEUl PPS2_E_ vE_ ڈ ۈ ܈ ܈ ݈ impleBatchIteratorImplINS_ parseBatchIteratorImplINS0_24ExternalMemoryPrefetcherINS_ 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1EllpackPageEEE ݈ BatchIteratorImplINS_ GraphvizGeneratorE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1EllpackPageEEE ݈ ވ ވ ߈ ߈ 1 7CSCPageEEES3_EE 0SparsePageEEES3_EE 3SortedCSCPageEEES3_EE 1EllpackPageEEES3_EE PPS5_E_NS_9allocatorISC_EEFbSB_EEE vE_NS_9allocatorISA_EEFvvEEE PPS2_E_ vE_ PPS5_E_NS_9allocatorISC_EEFbSB_EEE vE_NS_9allocatorISA_EEFvvEEE PPS2_E_ vE_ 4 1 6MetricEPKcEEE 9PredictorEPKNS2_16GenericParameterEEEE data16SparsePageFormatINS2_ tree14SplitEvaluatorENS_10unique_ptrIS4_NS_14default_deleteIS4_EEEEEEE 1 7CSCPageEEEvEEE 0SparsePageEEEvEEE 3SortedCSCPageEEEvEEE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEEE 6vectorIiNS2_9allocatorIiEEEEEE 12basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEEEES9_EE 6vectorIiNS3_9allocatorIiEEEEEES7_EE 5GradientBoosterEPKNS2_17LearnerModelParamEEEE 3 1 gbm obj 8GBLinearE 1 6GBTreeE 4DartE 3GBLinearModelE 1GBTreeModelE 5TreeProcessTypeEEE 3 0TreeMethodEEE PredictorTypeEEE DataSplitModeEEE ဉ Ђ Ԃ 삉 ȃ 색 Ԅ 녉 Ȇ LinearUpdaterEvEEE TreeGeneratorERKNS2_10FeatureMapENS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEEbEEE 1 2 7CoordinateUpdaterE 5FeatureSelectorE 4ShotgunUpdaterE 抉 LinearUpdaterE T JsonGeneratorE 1 2 CyclicFeatureSelectorE GreedyFeatureSelectorE RandomFeatureSelectorE ShuffleFeatureSelectorE ThriftyFeatureSelectorE Ō 1 7Eval 9EvalAucPRE 8Eval 2 3Eval 4Eval 6EvalMultiLogLossE EWiseBaseINS0_ PrecisionE 1 20EvalPoissonNegLogLikEEE 9EvalErrorEEE 1EvalRow 2EvalRowRMSLEEEE 0EvalRowMAEEEE 4EvalRowLogLossEEE 7EvalGammaDevianceEEE 6EvalGammaNLogLikEEE 8EvalTweedieNLogLikEEE RMSEEEE MPHEEEE Ɛ 䕉 ߙ M RankConfigE atchErrorE ClassBaseINS0_1 4EvalMatchErrorEEE 6EvalMultiLogLossEEE 柉 A MAPE CoxE MSE ucE ١ ᢉ 飉 RankE NDCGE ȧ Ш 0AFTNLogLikDispatcherE 1EvalEWiseSurvivalBaseINS0_ 14EvalAFTNLogLikINS_6common 30EvalIntervalRegressionAccuracyEEE 1 20LogisticDistributionEEEEE 8NormalDistributionEEEEE 9ExtremeDistributionEEEEE ŭ ObjFunctionEvEEE TreeUpdaterEvEEE ү 6AFTObjE 8HingeObjE 20SoftmaxMultiClassObjE 1 겉 3 0RegLossObjINS0_ 7 5GammaRegressionE LambdaRankObjINS0_2 CoxRegressionE 8PairwiseLambdaWeightComputerEEE 4NDCGLambdaWeightComputerEEE 3MAPLambdaWeightComputerEEE 鶉 1 22LogisticClassificationEEE 6 5SquaredLogErrorEEE 8LogisticRegressionEEE 1LogisticRawEEE LinearSquareLossEEE PseudoHuberErrorEEE ͼ ｉ PoissonRegressionE TweedieRegressionE É ĉ ʼn lj lj ȉ 1 8ColMaker 9 2 4SplitEvaluatorE 0 9MonotonicConstraintE 1 7QuantileHistMaker 6HistSynchronizerI 3 8BatchHistRowsAdderI ȉ ʉ ElasticNetE TreePrunerE ˉ ̉ ω ω ω Љ Љ щ щ ҉ ҉ Ӊ Ӊ Ӊ ԉ ։ extGeneratorE reeGeneratorE basic_stringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE __ ܠ ى ډ ۉ ܉ ݉ E 7BuilderE ݉ ݉ މ މ CQHistMakerE SketchMakerE TreeSyncherE HistMakerE BaseMakerE 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_ 3TreeRefresher6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEEEUlvE_ 3GlobalProposalHistMakerE 7DistributedHistSynchronizerI 4DistributedHistRowsAdderI 1BatchHistSynchronizerI E 7BuilderI fEE dEE fEE dEE fEE dEE fEE dEE HistRowsAdderI TreeRefresherE fEE dEE fEE dEE fEE dEE bN7xgboost4tree17QuantileHistMaker7BuilderI vvENS_9allocatorIS3_EES2_EE ޝ fE11ExpandEntryES7_ENS_9allocatorIS9_EES8_EE dE11ExpandEntryES7_ENS_9allocatorIS9_EES8_EE fE11ExpandEntryES7_EEE dE11ExpandEntryES7_EEE bN7xgboost4tree17QuantileHistMaker7BuilderI vvE fE11ExpandEntryES4_E dE11ExpandEntryES4_E bN7xgboost4tree17QuantileHistMaker7BuilderI vvE fE11ExpandEntryES4_E dE11ExpandEntryES4_E 1 7IEngineE 3AllreduceBaseE 5AllreduceRobustE assoc_stateIbEE empty_stateIcEE 1ReadWrapperE 2WriteWrapperE 1 9CSVParserI 1 2 4T 0ParserImplI Ќ DiskRowIterI LibFMParserI j y ʀ fEE iEE xEE j y fEE iEE xEE _ t3__16vectorINS_4data17RowBlockContainerI 8RowBlockI 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEE j y fEEEE iEEEE xEEEE _ t3__16vectorINS_4data17RowBlockContainerI 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEE j y fEEEE iEEEE xEEEE ƈ j y fEEEE iEEEE xEEEE ͈ 4data1 2io1 1DiskRowIterI 4ThreadedParserI ώ j y fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl Ԉ PPNS3_17RowBlockContainerIjfEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEEE j y fEEEEE iEEEEE xEEEEE 4data1 2io1 1DiskRowIterI 4ThreadedParserI ߐ j y fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl É PPNS0_17RowBlockContainerIjfEEE_ vE_ BasicRowIterI LibSVMParserI j y ݄ fEE ÀiEE φxEE fEE iEE ֆxEE fEE iEE ݆xEE fEEEE iEEEE xEEEE Ɂ fEEEE ǁiEEEE xEEEE 큊 fEEEE iEEEE xEEEE fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS3_17RowBlockContainerIyfEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE τ fEEEEE ǃiEEEEE xEEEEE ߃ fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS0_17RowBlockContainerIyfEEE_ ȄvE_ ք ޅ fEE iEE xEE φ 醊 Ň PPNS3_17RowBlockContainerIjiEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE PPNS0_17RowBlockContainerIjiEEE_ vE_ Ȇʼn ы 匊 PPNS3_17RowBlockContainerIyiEEE_NS_9allocatorISA_EEFbS9_EEE ڇvE_NS_9allocatorIS6_EEFvvEEE PPNS0_17RowBlockContainerIyiEEE_ vE_ 厊 Ґ ͑ PPNS3_17RowBlockContainerIjxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE PPNS0_17RowBlockContainerIjxEEE_ vE_ ֔ ɖ 햊 PPNS3_17RowBlockContainerIyxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE ҋؗ ߘ PPNS0_17RowBlockContainerIyxEEE_ ˋvE_ ً ޚ jfEE yfEE extParserBaseI hreadedParserI j y fEE ɌiEE xEE Л j ܌y fEE iEE xEE j y ђ fEE iEE xEE jfEE yfEE jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE jfEENS1_9allocatorIS5_EEEEEE ȎyfEENS1_9allocatorIS5_EEEEEE jfEC1EPNS3_10ParserImplIjfEEEUl yfEC1EPNS3_10ParserImplIyfEEEUl PPNS_6vectorINS3_17RowBlockContainerIjfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE jfEENS_9allocatorIS6_EEEEEEE ؐyfEENS_9allocatorIS6_EEEEEEE jfEC1EPNS0_10ParserImplIjfEEEUl yfEC1EPNS0_10ParserImplIyfEEEUl PPNSt3__16vectorINS0_17RowBlockContainerIjfEENS6_9allocatorIS9_EEEEE_ vE_ fEE iEE xEE ܢ fEE ʒiEE xEE fEE iEE xEE Σ PPNS_6vectorINS3_17RowBlockContainerIyfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE PPNSt3__16vectorINS0_17RowBlockContainerIyfEENS6_9allocatorIS9_EEEEE_ ܔvE_ jfEE yfEE ɩ 穊 j y fEE iEE ٕxEE fEE ҕiEE xEE ֪ « 㫊 Ϭ 쬊 ح 1 23IndexedRecordIOSplitterE 5 8ThreadedInputSplitE 6 2LineSplitterE 4InputSplitBaseE 0FileS Ѣ SingleFileSplitE LocalFileSystemE ߮ 8ThreadedInputSplitC1EPNS3_14InputSplitBaseEmEUl ۘ6CachedInputSplit1 PPNS5_5ChunkEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS7_EEFvvEEE į Ű 8ThreadedInputSplitC1EPNS0_14InputSplitBaseEmEUl 6CachedInputSplit1 PPNS2_5ChunkEE_ vE_ ӱ Ʋ CachedInputSplitE RecordIOSplitterE 4InitCachedIterEvEUl ֛5InitPreprocIterEvEUlPPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE Н PPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE vE_NS_9allocatorIS5_EEFvvEEE 4InitCachedIterEvEUl 5InitPreprocIterEvEUlPPNS0_14InputSplitBase5ChunkEE_ ם PPNS0_14InputSplitBase5ChunkEE_ vE_ ɝ 㵊 ϸ 츊 end_stateIcEE lookaheadIcNS_12regex_traitsIcEEEE ΠalternateIcEE match_anyIcEE ʢ nodeIcEE loopIcEE Թ 繊 ˺ owns_one_stateIcEE back_ref_icaseIcNS_12regex_traitsIcEEEE ͡ has_one_stateIcEE word_boundaryIcNS_12regex_traitsIcEEEE Ǡ һ 껊 ⼊ match_char_icaseIcNS_12regex_traitsIcEEEE back_ref_collateIcNS_12regex_traitsIcEEEE ԡ Ŀ owns_two_statesIcEE repeat_one_loopIcEE ystemE treamE N ZN F PF Ԅ 4dmlc 7xgboost St3__1 5rabit 5ErrorE 8DataIterIN 6 ܶ1 7istream 9parameter1 4data ̉2io 7xgboost S 4data ɤ1 7CSCPageEEE 1 21DataTableAdapterBatchEEE 6FileAdapterBatchEEE 5CS 7DenseAdapterBatchEEE 4 6 5 1 9 8JsonNullE 7 3 20LearnerConfigurationE data tree 1 6detail19SingleBatchDataIterINS0_ Ѳ2 5IteratorAdapterIPvFiS2_PFiS2_15XGBoostBatchCSRES2_ES3_EE 2D 0CS ɳ6 1FileAdapterE 3SimpleDMatrixE 7SparsePageDMatrixE 9SparsePageRawFormatINS_ MatrixProxyE enseAdapterE 2 1 6__ 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 ȳbracket_expressionIcNS_12regex_traitsIcEEEE pointerIPN emplaceIN7xgboost16HostDeviceVectorIjEENS_9allocatorIS3_EEEE 7xgboost ΫS_13__empty_stateIcEENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 1 7DMatrixENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE Ƹ4data1 8JsonNullENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 9JsonArrayENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 7BatchIteratorImplINS1_ 0 ڴ1Json 1 7CSCPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE ϯ 0SparsePageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE ȯ3SortedCSCPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE ֯1EllpackPageEEENS_14default_deleteIS4_EENS_9allocatorIS4_EEEE ݯÐ Ð Đ Đ
+9basic_ ذ5 ձ0 4basic_ifstreamIcNS_11char_traitsIcEEEE 3 ſ8 7 1__ 6__ 2__match_charIcEE ϳ ostringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE αistringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE նƐ basic_stringbufIcNS_11char_traitsIcEENS_9allocatorIcEEEE __ ǐ RAdapterBatchEEE ʲCAdapterBatchEEE Ȑ 1 21DataTableAdapterBatchEEE 5CS 7DenseAdapterBatchEEE RAdapterBatchEEE ³CAdapterBatchEEE Ȑ RAdapterE CAdapterE ɐ ɐ ɐ ʐ ʐ ː ː ː ̐ DataTableAdapterE ӴSparsePageFormatINS_ ̐ Json SparsePageENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE ObjectENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE ζStringENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE NumberENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE ͐ ΐ StreamE ParserI Ӝϐ 0 2 SeekStreamE ParamErrorE InputSplitE ϐ 5 Ϸ6engine utils1 c_api1 9MemoryFixSizeBufferE 8MemoryBufferStreamE ϐ А E 5InBufE Ґ Ӑ Ԑ 2D 0CSRAdapterENS_14default_deleteIS3_EENS_9allocatorIS3_EEEE MatrixProxyENS_14default_deleteIS3_EENS_9allocatorIS3_EEEE enseAdapterENS_14default_deleteIS3_EENS_9allocatorIS3_EEEE Ԑ Ր shared_ptrIN7xgboost4data1 ź__ 2DenseAdapterEEE 0CSRAdapterEEE Ր 7xgboost 5rabit6engine1 4dmlc2io ߮ 6common 1 9 8JsonNullE 7 4 3gbm 1 9DenseCutsE 0SparseCutsE 5FixedSizeStreamE 6PeekableInStreamE common linear MetricE metric 1 9DenseCutsE 6ColumnI 1 0SparseCutsE 2SparseColumnI ھ6PeekableInStreamE 5FixedSizeStreamE CutsBuilderE DenseColumnI א hEE tEE jEE א hEE ӾtEE jEE א hEE tEE jEE ؐ ؐ ؐ ِ ِ ِ ڐ ڐ ڐ ې ې ݐ basic_filebufIcNS_11char_traitsIcEEEE __ ސ 0Json 1Json ObjectE StringE NumberE ReaderE WriterE ސ JsonArrayE PredictorE ߐ ߐ ValueE ModelE 0Json 1 7 2ConfigurableE 5GradientBoosterE 3 StringE ObjectE NumberE ReaderE WriterE JsonArrayE LearnerIOE predictor12CPUPredictorE PredictorE IntegerE BooleanE Json LearnerImplE ObjFunctionE TreeUpdaterE IntegerE BooleanE IntegerENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE BooleanENS_14default_deleteIS2_EENS_9allocatorIS2_EEEE 6FieldAccessEntryE 4FieldEntryBaseINS0_10FieldEntryI 7FieldEntryNumericINS0_10FieldEntryI 0FieldEntryI iEEiEE fEEfEE NSt3__1 mEEmEE bEEbEE jEEjEE xEExEE dEEdEE iEEiEE fEEfEE mEEmEE jEEjEE xEExEE dEEdEE iEE N fEE mEE bEE jEE xEE dEE 7xgboost St3__1 6common27ProbabilityDistributionTypeEEE 1 basic_stringstreamIcNS_11char_traitsIcEENS_9allocatorIcEEEE __ DMatrixE LearnerE RegTreeE DMatrixE LearnerE RegTreeE bad_function_callE __ 0SparsePageEEE 3SortedCSCPageEEE 4ExternalMemoryPrefetcherINS_ 3S 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE ThreadedIterIN S RowBlockIterI 7xgboost S 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE copedThreadE erializableE function6__ l_anchorIcEE ²r_anchorIcEE ɲback_refIcEE baseIF funcI b vvEEE PN7xgboost PPN N7xgboost4tree17QuantileHistMaker7BuilderI 7xgboost 4dmlc S_6vectorIN4dmlc4data17RowBlockContainerI 1 7CSCPageEEEE 0SparsePageEEEE 3SortedCSCPageEEEE ZN PF 7xgboost4 4dmlc data24ExternalMemoryPrefetcherINS2_ tree1 1 7CSCPageEEC1ERKNS3_9CacheInfoEEUl 0SparsePageEEC1ERKNS3_9CacheInfoEEUl 3SortedCSCPageEEC1ERKNS3_9CacheInfoEEUl PPS5_E_NS_9allocatorISC_EEFbSB_EEE vE_NS_9allocatorISA_EEFvvEEE 7xgboost4 4dmlc data24ExternalMemoryPrefetcherINS_ tree1 1 7CSCPageEEC1ERKNS0_9CacheInfoEEUl 0SparsePageEEC1ERKNS0_9CacheInfoEEUl 3SortedCSCPageEEC1ERKNS0_9CacheInfoEEUl PPS2_E_ vE_ data1 tree1 3SimpleDMatrixE 7SparsePageDMatrixE BatchIteratorImplINS_ GraphvizGeneratorE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1EllpackPageEEE impleBatchIteratorImplINS_ parseBatchIteratorImplINS0_24ExternalMemoryPrefetcherINS_ 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE 1EllpackPageEEE 1 7CSCPageEEES3_EE 0SparsePageEEES3_EE 3SortedCSCPageEEES3_EE 1EllpackPageEEES3_EE PPS5_E_NS_9allocatorISC_EEFbSB_EEE vE_NS_9allocatorISA_EEFvvEEE PPS2_E_ vE_ Є PPS5_E_NS_9allocatorISC_EEFbSB_EEE vE_NS_9allocatorISA_EEFvvEEE PPS2_E_ vE_ ؆ ؇ 4 1 6MetricEPKcEEE 9PredictorEPKNS2_16GenericParameterEEEE data16SparsePageFormatINS2_ tree14SplitEvaluatorENS_10unique_ptrIS4_NS_14default_deleteIS4_EEEEEEE 1 7CSCPageEEEvEEE 0SparsePageEEEvEEE 3SortedCSCPageEEEvEEE 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE Њ 1 7CSCPageEEE 0SparsePageEEE 3SortedCSCPageEEE Ќ Ѝ 12basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEEEES9_EE 6vectorIiNS3_9allocatorIiEEEEEES7_EE ȏ 12basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEEE 6vectorIiNS2_9allocatorIiEEEEEE ȑ 5GradientBoosterEPKNS2_17LearnerModelParamEEEE 3 1 蒑 蔑 gbm obj 8GBLinearE 1 6GBTreeE 4DartE 1 6GBTreeE 3GBLinearModelE 1GBTreeModelE 蕑 3GBLinearModelE 1GBTreeModelE 5TreeProcessTypeEEE 3 0TreeMethodEEE PredictorTypeEEE DataSplitModeEEE Ƞ ȣ ح 译 LinearUpdaterEvEEE TreeGeneratorERKNS2_10FeatureMapENS_12basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEEbEEE LinearUpdaterE T JsonGeneratorE 1 2 7CoordinateUpdaterE 5FeatureSelectorE 4ShotgunUpdaterE в 1 2 CyclicFeatureSelectorE GreedyFeatureSelectorE RandomFeatureSelectorE ShuffleFeatureSelectorE ThriftyFeatureSelectorE ض ط ȸ 1 7Eval 9EvalAucPRE 8Eval 2 3Eval 4Eval 6EvalMultiLogLossE EWiseBaseINS0_ PrecisionE 1 20EvalPoissonNegLogLikEEE 9EvalErrorEEE 1EvalRow 2EvalRowRMSLEEEE 0EvalRowMAEEEE 4EvalRowLogLossEEE 7EvalGammaDevianceEEE 6EvalGammaNLogLikEEE 8EvalTweedieNLogLikEEE RMSEEEE MPHEEEE ฑ ࿑ Ñ ő Ƒ ȑ M RankConfigE ClassBaseINS0_1 atchErrorE 4EvalMatchErrorEEE 6EvalMultiLogLossEEE ʑ ʑ ̑ ̑ A MAPE CoxE MSE ucE Α ϑ ё ӑ RankE NDCGE ӑ ԑ ֑ ؑ ڑ 0AFTNLogLikDispatcherE 1EvalEWiseSurvivalBaseINS0_ ۑ 14EvalAFTNLogLikINS_6common 30EvalIntervalRegressionAccuracyEEE 1 20LogisticDistributionEEEEE 8NormalDistributionEEEEE 9ExtremeDistributionEEEEE ܑ ݑ ޑ ߑ ObjFunctionEvEEE TreeUpdaterEvEEE 6AFTObjE 8HingeObjE 20SoftmaxMultiClassObjE 1 3 0RegLossObjINS0_ 7 5GammaRegressionE LambdaRankObjINS0_2 CoxRegressionE 8PairwiseLambdaWeightComputerEEE 4NDCGLambdaWeightComputerEEE 3MAPLambdaWeightComputerEEE 1 22LogisticClassificationEEE 6 5SquaredLogErrorEEE 8LogisticRegressionEEE 1LogisticRawEEE LinearSquareLossEEE PseudoHuberErrorEEE PoissonRegressionE TweedieRegressionE 4SplitEvaluatorE 7QuantileHistMaker 1 8ColMaker 9 2 4SplitEvaluatorE 0 9MonotonicConstraintE 1 7QuantileHistMaker 6HistSynchronizerI 3 8BatchHistRowsAdderI ElasticNetE TreePrunerE 膒 Ȋ Ȍ Ѝ reeGeneratorE extGeneratorE ؑ ؓ ؔ ؕ E 7BuilderE BaseMakerE HistMakerE CQHistMakerE SketchMakerE TreeSyncherE Й 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_ 3TreeRefresher6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKNSt3__16vectorIPNS_7RegTreeENSA_9allocatorISD_EEEEEUlvE_ 3GlobalProposalHistMakerE 7DistributedHistSynchronizerI 4DistributedHistRowsAdderI 1BatchHistSynchronizerI ؞ Ƞ 7BuilderI E fEE dEE E 7BuilderI fEE dEE fEE dEE Áآ fEE dEE ʁ袒 HistRowsAdderI TreeRefresherE fEE dEE с fEE dEE fEE dEE ߁ fEE dEE ȥ إ ئ fE11ExpandEntryES7_EEE dE11ExpandEntryES7_EEE Ņȧ bN7xgboost4tree17QuantileHistMaker7BuilderI vvENS_9allocatorIS3_EES2_EE ʮ fE11ExpandEntryES7_ENS_9allocatorIS9_EES8_EE ܃dE11ExpandEntryES7_ENS_9allocatorIS9_EES8_EE ̅ا bN7xgboost4tree17QuantileHistMaker7BuilderI vvE Ѯ fE11ExpandEntryES4_E ̈́dE11ExpandEntryES4_E Ӆ bN7xgboost4tree17QuantileHistMaker7BuilderI vvE خ fE11ExpandEntryES4_E dE11ExpandEntryES4_E څ 3AllreduceBaseE 5AllreduceRobustE 7IEngineE Ɇ1 Іг 3AllreduceBaseE 5AllreduceRobustE assoc_stateIbEE empty_stateIcEE 赒 1ReadWrapperE 2WriteWrapperE ȶ _ t3__16vectorINS_4data17RowBlockContainerI 8RowBlockI 4data17RowBlockContainerI Њ2io14InputSplitBase5ChunkEEE j y fEEEE iEEEE xEEEE 跒 j y ڑ fEE ʼniEE xEE 1 9CSVParserI 1 2 0ParserImplI 4T DiskRowIterI LibFMParserI ݥ j y fEE ɊiEE xEE j ܊y fEEEE iEEEE xEEEE ฒ _ t3__16vectorINS_4data17RowBlockContainerI 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEE j y fEEEE iEEEE xEEEE 4data17RowBlockContainerI 2io14InputSplitBase5ChunkEEEE j y ޒ fEEEEE iEEEEE xEEEEE ๒ 4data1 2io1 1DiskRowIterI э4ThreadedParserI j ݍy fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl Ǚ PPNS3_17RowBlockContainerIjfEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE ڐ 4data1 2io1 1DiskRowIterI ͏4ThreadedParserI ˡ j ُy fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS0_17RowBlockContainerIjfEEE_ ӐvE_ BasicRowIterI LibSVMParserI j y ɕ fEE iEE xEE ػ fEEEE ӑiEEEE xEEEE fEE iEE ɗxEE fEE iEE ЗxEE ؼ fEEEE iEEEE חxEEEE fEEEE גiEEEE ޗxEEEE fEEEEE iEEEEE xEEEEE fE12TryLoadCacheEvEUl ғiE12TryLoadCacheEvEUl xE12TryLoadCacheEvEUl PPNS3_17RowBlockContainerIyfEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE fE12TryLoadCacheEvEUl iE12TryLoadCacheEvEUl ԘxE12TryLoadCacheEvEUl PPNS0_17RowBlockContainerIyfEEE_ vE_ о п fEE iEE xEE ̜ PPNS3_17RowBlockContainerIjiEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE Ò PPNS0_17RowBlockContainerIjiEEE_ vE_ Ò Ē Ē Ē Œ Œ Œ ƒ ƒ ǒ PPNS3_17RowBlockContainerIyiEEE_NS_9allocatorISA_EEFbS9_EEE ͘vE_NS_9allocatorIS6_EEFvvEEE ǒ PPNS0_17RowBlockContainerIyiEEE_ vE_ ǒ Ȓ Ȓ ɒ ʒ ʒ ʒ ˒ ˒ ̒ PPNS3_17RowBlockContainerIjxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE ̒ PPNS0_17RowBlockContainerIjxEEE_ ܚvE_ ̒ ͒ ͒ ͒ Β Β Β ϒ ϒ В PPNS3_17RowBlockContainerIyxEEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS6_EEFvvEEE В PPNS0_17RowBlockContainerIyxEEE_ vE_ ŜВ ђ ђ Ғ j ߜy fEE iEE ŦxEE Ӓ j y fEE iEE ̦xEE Ӓ extParserBaseI ͝hreadedParserI j ٝy fEE iEE ӦxEE Ӓ jfEE yfEE ԣӒ jfEE yfEE ۣՒ jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE ֒ jfEENS1_9allocatorIS5_EEEEEE yfEENS1_9allocatorIS5_EEEEEE ֒ jfEENS_9allocatorIS6_EEEEEEE yfEENS_9allocatorIS6_EEEEEEE ג jfEC1EPNS3_10ParserImplIjfEEEUl ̠yfEC1EPNS3_10ParserImplIyfEEEUl PPNS_6vectorINS3_17RowBlockContainerIjfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE ġvE_NS_9allocatorIS9_EEFvvEEE ג jfEC1EPNS0_10ParserImplIjfEEEUl yfEC1EPNS0_10ParserImplIyfEEEUl PPNSt3__16vectorINS0_17RowBlockContainerIjfEENS6_9allocatorIS9_EEEEE_ vE_ ג ؒ ؒ fEE iEE xEE ْ fEE iEE xEE ْ fEE ͣiEE xEE ْ ڒ ܒ ܒ ܒ ݒ PPNS_6vectorINS3_17RowBlockContainerIyfEENS_9allocatorISB_EEEEE_NSC_ISH_EEFbSG_EEE vE_NS_9allocatorIS9_EEFvvEEE ϥݒ PPNSt3__16vectorINS0_17RowBlockContainerIyfEENS6_9allocatorIS9_EEEEE_ ȥvE_ ֥ݒ ޒ ޒ jfEE yfEE ߒ j y fEE iEE ڦxEE fEE iEE xEE 1 23IndexedRecordIOSplitterE 5 8ThreadedInputSplitE 6 2LineSplitterE 4InputSplitBaseE 0FileS SingleFileSplitE ߨLocalFileSystemE 8ThreadedInputSplitC1EPNS3_14InputSplitBaseEmEUl Ω6CachedInputSplit1 ի PPNS5_5ChunkEE_NS_9allocatorISA_EEFbS9_EEE vE_NS_9allocatorIS7_EEFvvEEE 8ThreadedInputSplitC1EPNS0_14InputSplitBaseEmEUl 6CachedInputSplit1 PPNS2_5ChunkEE_ vE_ CachedInputSplitE ΫRecordIOSplitterE 4InitCachedIterEvEUl ¬5InitPreprocIterEvEUlPPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE PPNS3_14InputSplitBase5ChunkEE_NS_9allocatorIS9_EEFbS8_EEE vE_NS_9allocatorIS5_EEFvvEEE 4InitCachedIterEvEUl 5InitPreprocIterEvEUlPPNS0_14InputSplitBase5ChunkEE_ î PPNS0_14InputSplitBase5ChunkEE_ vE_ 1 23IndexedRecordIOSplitterE 2LineSplitterE 6RecordIOSplitterE 4InputSplitBaseE 0FileSystemE ڴ5LocalFileSystemE nodeIcEE loopIcEE end_stateIcEE lookaheadIcNS_12regex_traitsIcEEEE ײalternateIcEE Ŵmatch_anyIcEE Ӵ has_one_stateIcEE word_boundaryIcNS_12regex_traitsIcEEEE в owns_one_stateIcEE back_ref_icaseIcNS_12regex_traitsIcEEEE ֳ Ȁ match_char_icaseIcNS_12regex_traitsIcEEEE back_ref_collateIcNS_12regex_traitsIcEEEE ݳ 肓 Ѕ owns_two_statesIcEE repeat_one_loopIcEE ȉ ystemE treamE 16ThreadLocalStoreI 3any8TypeInfoINSt3__110shared_ptrIN7xgboost4data1 2io15LocalFileSystem11GetInstanceEvE8instance N 16XGBAPIErrorEntryE3GetEvE4inst 7xgboost St3__13mapIPKN7xgboost7 ػ 19LogCallbackRegistryEE3GetEvE4inst 6common22RandomThreadLocalEntryEE3GetEvE4inst ʻ VZN RZN7xgboost13TextGenerator9BuildTreeERKNS_7RegTreeEE13kTreeTemplate_ 4dmlc K7xgboost 7xgboost1 5rabit16ThreadLocalStoreINS_6engine16ThreadLocalEntryEE9SingletonEvE4inst 16ThreadLocalStoreI 3any8TypeInfoINSt3__110shared_ptrIN7xgboost4data1 2io15LocalFileSystem11GetInstanceEvE8instance N 16XGBAPIErrorEntryE3GetEvE4inst û 7xgboost ۺSt3__13mapIPKN7xgboost7 ܼ 19LogCallbackRegistryEE3GetEvE4inst 6common22RandomThreadLocalEntryEE3GetEvE4inst ѻ ، DMatrixENS3_22XGBAPIThreadLocalEntryENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst ռLearnerENS3_ DMatrixENS3_22XGBAPIThreadLocalEntryENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst ٽLearnerENS3_ 19PredictionContainerENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst 22XGBAPIThreadLocalEntryENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst 19PredictionContainerENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst 22XGBAPIThreadLocalEntryENS1_4lessIS6_EENS1_9allocatorINS1_4pairIKS6_S7_EEEEEEE3GetEvE4inst Ѝ 荓 3GetEvE3ptr 9SingletonEvE4inst 2DenseAdapterEEEE8get_typeEvE2tp 0CSRAdapterEEEE8get_typeEvE2tp 2DenseAdapterEEEE8get_typeEvE2tp 0CSRAdapterEEEE8get_typeEvE2tp Ȏ Ў 莓 6metric 1 9EvalError4NameEvE4name 18EvalTweedieNLogLik4NameEvE4name 蒓 6metric 1 9EvalError4NameEvE4name 18EvalTweedieNLogLik4NameEvE4name 3 7GraphvizGenerator TextGenerator JsonGenerator 9 7IntegerERKNS_7RegTreeEijE16kIntegerTemplate 10QuantitiveERKNS_7RegTreeEijE19kQuantitiveTemplate 8 IndicatorERKNS_7RegTreeEijE18kIndicatorTemplate PlainNodeERKNS_7RegTreeEijE13kNodeTemplate З 3 7GraphvizGenerator TextGenerator JsonGenerator 9 7IntegerERKNS_7RegTreeEijE16kIntegerTemplate 10QuantitiveERKNS_7RegTreeEijE19kQuantitiveTemplate 8 IndicatorERKNS_7RegTreeEijE18kIndicatorTemplate PlainNodeERKNS_7RegTreeEijE13kNodeTemplate 藓 NodeStatERKNS_7RegTreeEiE13kStatTemplate LeafNodeERKNS_7RegTreeEijE13k NodeStatERKNS_7RegTreeEiE13kStatTemplate LeafNodeERKNS_7RegTreeEijE13k Ș И 蘓 LeafTemplate StatTemplate LeafTemplate StatTemplate TextGenerator9BuildTreeERKNS_7RegTreeE JsonGenerator9 ijE13kNodeTemplate E13kTreeTemplate 3 7GraphvizGenerator TextGenerator9BuildTreeERKNS_7RegTreeE JsonGenerator9 ijE13kNodeTemplate E13kTreeTemplate ș Й ؙ 9 7IntegerERKNS_7RegTreeEijE16kIntegerTemplate 10QuantitiveERKNS_7RegTreeEijE19kQuantitiveTemplate 8 IndicatorERKNS_7RegTreeEijE18kIndicatorTemplate PlainNodeERKNS_7RegTreeEijE13kNodeTemplate 9 7IntegerERKNS_7RegTreeEijE16kIntegerTemplate 10QuantitiveERKNS_7RegTreeEijE19kQuantitiveTemplate 8 IndicatorERKNS_7RegTreeEijE18kIndicatorTemplate PlainNodeERKNS_7RegTreeEijE13kNodeTemplate К NodeStatERKNS_7RegTreeEiE13kStatTemplate LeafNodeERKNS_7RegTreeEijE13k ؚ NodeStatERKNS_7RegTreeEiE13kStatTemplate LeafNodeERKNS_7RegTreeEijE13k SplitNodeERKNS_7RegTreeEijE18kSplitNodeTemplate BuildTreeERKNS_7RegTreeEijE13kNodeTemplate SplitNodeERKNS_7RegTreeEijE18kSplitNodeTemplate 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__ZN4dmlc4data14TextParserBaseIjiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjiEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIyiEC2EPNS_10InputSplitEi.cold.1 __ZN4dmlc4data14TextParserBaseIyiED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIyiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyiEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIyiE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIyiEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIjxEC2EPNS_10InputSplitEi.cold.1 __ZN4dmlc4data14TextParserBaseIjxED2Ev.cold.1 __ZN4dmlc4data14TextParserBaseIjxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjxEENS3_9allocatorIS6_EEEE.cold.1 __ZN4dmlc4data14TextParserBaseIjxE8FillDataEPNSt3__16vectorINS0_17RowBlockContainerIjxEENS3_9allocatorIS6_EEEE.cold.2 __ZN4dmlc4data14TextParserBaseIyxEC2EPNS_10InputSplitEi.cold.1 __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 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