- 13 Sep, 2023 2 commits
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James Lamb authored
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James Lamb authored
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- 04 Sep, 2023 1 commit
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Pavel Metrikov authored
* Update dataset.h * Update metadata.cpp * Update rank_objective.hpp * Update metadata.cpp * Update rank_objective.hpp * Update metadata.cpp * Update dataset.h * Update rank_objective.hpp * Update metadata.cpp * Update test_engine.py * Update test_engine.py * Add files via upload * Update test_engine.py * Update test_engine.py * Update test_engine.py * Update test_engine.py * Update test_engine.py * Update _rank.train.position * Update test_engine.py * Update test_engine.py * Update test_engine.py * Update test_engine.py * Update _rank.train.position * Update _rank.train.position * Update test_engine.py * Update _rank.train.position * Update test_engine.py * Update test_engine.py * Update test_engine.py * Update test_engine.py * Update test_engine.py * Update the position of import statement * Update rank_objective.hpp * Update config.h * Update config_auto.cpp * Update rank_objective.hpp * Update rank_objective.hpp * update documentation * remove extra blank line * Update src/io/metadata.cpp Co-authored-by:
James Lamb <jaylamb20@gmail.com> * Update src/io/metadata.cpp Co-authored-by:
shiyu1994 <shiyu_k1994@qq.com> Co-authored-by:
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- 19 Aug, 2023 1 commit
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James Lamb authored
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- 15 Aug, 2023 1 commit
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Zachary Huang authored
* Update regression_objective.hpp * Update regression_objective.hpp Maybe still need a (1.0 - alpha) * fix position in percentile calculation * fix regression metric threshold for l1 --------- Co-authored-by:
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- 16 May, 2023 1 commit
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James Lamb authored
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- 05 May, 2023 1 commit
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shiyu1994 authored
* add quantized training (first stage) * add histogram construction functions for integer gradients * add stochastic rounding * update docs * fix compilation errors by adding template instantiations * update files for compilation * fix compilation of gpu version * initialize gradient discretizer before share states * add a test case for quantized training * add quantized training for data distributed training * Delete origin.pred * Delete ifelse.pred * Delete LightGBM_model.txt * remove useless changes * fix lint error * remove debug loggings * fix mismatch of vector and allocator types * remove changes in main.cpp * fix bugs with uninitialized gradient discretizer * initialize ordered gradients in gradient discretizer * disable quantized training with gpu and cuda fix msvc compilation errors and warnings * fix bug in data parallel tree learner * make quantized training test deterministic * make quantized training in test case more accurate * refactor test_quantized_training * fix leaf splits initialization with quantized training * check distributed quantized training result
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- 25 Apr, 2023 1 commit
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James Lamb authored
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- 19 Apr, 2023 1 commit
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James Lamb authored
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- 30 Mar, 2023 1 commit
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James Lamb authored
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- 21 Mar, 2023 1 commit
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shiyu1994 authored
* add cuda quantile regression objective * remove white space * resolve merge conflicts * remove useless changes * remove useless changes * enable cuda quantile regression objective * add a test case for quantile regression objective * remove useless changes * remove useless changes * reduce DP_SHARED_HIST_SIZE to 5176 for CUDA 10 --------- Co-authored-by:
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- 16 Mar, 2023 1 commit
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shiyu1994 authored
Co-authored-by:
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- 01 Feb, 2023 1 commit
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James Lamb authored
* [ci] speed up if-else, swig, and lint conda setup * add 'source activate' * python constraint * start removing cuda v1 * comment out CI * remove more references * revert some unnecessaary changes * revert a few more mistakes * revert another change that ignored params * sigh * remove CUDATreeLearner * fix tests, docs * fix quoting in setup.py * restore all CI * Apply suggestions from code review Co-authored-by:
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- 12 Jan, 2023 1 commit
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James Lamb authored
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- 30 Dec, 2022 1 commit
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Belinda Trotta authored
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- 28 Dec, 2022 1 commit
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Yifei Liu authored
* add parameter data_sample_strategy * abstract GOSS as a sample strategy(GOSS1), togetherwith origial GOSS (Normal Bagging has not been abstracted, so do NOT use it now) * abstract Bagging as a subclass (BAGGING), but original Bagging members in GBDT are still kept * fix some variables * remove GOSS(as boost) and Bagging logic in GBDT * rename GOSS1 to GOSS(as sample strategy) * add warning about use GOSS as boosting_type * a little ; bug * remove CHECK when "gradients != nullptr" * rename DataSampleStrategy to avoid confusion * remove and add some ccomments, followingconvention * fix bug about GBDT::ResetConfig (ObjectiveFunction inconsistencty bet… * add std::ignore to avoid compiler warnings (anpotential fails) * update Makevars and vcxproj * handle constant hessian move resize of gradient vectors out of sample strategy * mark override for IsHessianChange * fix lint errors * rerun parameter_generator.py * update config_auto.cpp * delete redundant blank line * update num_data_ when train_data_ is updated set gradients and hessians when GOSS * check bagging_freq is not zero * reset config_ value merge ResetBaggingConfig and ResetGOSS * remove useless check * add ttests in test_engine.py * remove whitespace in blank line * remove arguments verbose_eval and evals_result * Update tests/python_package_test/test_engine.py reduce num_boost_round Co-authored-by:
Nikita Titov <nekit94-08@mail.ru> * Update src/boosting/bagging.hpp Co-authored-by:
Guangda Liu <v-guangdaliu@microsoft.com> Co-authored-by:
GuangdaLiu <90019144+GuangdaLiu@users.noreply.github.com> Co-authored-by:
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- 13 Dec, 2022 1 commit
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José Morales authored
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- 27 Nov, 2022 1 commit
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shiyu1994 authored
[CUDA] Add Poisson regression objective for cuda_exp and refactor objective functions for cuda_exp (#5486) * add poisson regression objective for cuda_exp * enable Poisson regression for cuda_exp * refactor cuda objective functions * remove useless changes * fix linter errors * remove redundant buffer in cuda poisson regression objective * fix log of cuda_exp binary objective * fix threshold of poisson objective result * remove useless changes * fix compilation errors * add cuda quantile regression objective * remove cuda quantile regression objective Co-authored-by:
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- 11 Oct, 2022 2 commits
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José Morales authored
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José Morales authored
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- 07 Sep, 2022 2 commits
- 02 Sep, 2022 1 commit
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shiyu1994 authored
* add huber regression for cuda_exp * renew tree output on GPU add test cases for regression objectives * remove useless changes * add white space * fix test_regression
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- 28 Aug, 2022 1 commit
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José Morales authored
* ignore training set on early stopping callback * fixes * lint * Apply suggestions from code review Co-authored-by:
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- 16 Aug, 2022 1 commit
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nyanp authored
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- 29 Jul, 2022 1 commit
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Belinda Trotta authored
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- 03 Jul, 2022 1 commit
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José Morales authored
add validate_features to refit
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- 27 Jun, 2022 2 commits
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José Morales authored
* allow custom weighing in sklearn api * add suggestions from review Co-authored-by: -
José Morales authored
* check feature names and order in predict with dataframe * slice df in predict to remove the target * scramble features * handle int column names * only change column order when needed * include validate_features param in booster and sklearn estimators * document validate_features argument * use all_close in preds checks and check for assertion error to compare different arrays * perform remapping and checks in cpp * remove extra logs * fixes * revert cpp * proposal * remove extra arg * lint * restore _data_from_pandas arguments * Apply suggestions from code review Co-authored-by:
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- 08 Jun, 2022 1 commit
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shiyu1994 authored
Clear split info buffer in cost efficient gradient boosting before every iteration (fix partially #3679) (#5164) * clear split info buffer in cegb_ before every iteration * check nullable of cegb_ in serial_tree_learner.cpp * add a test case for checking the split buffer in CEGB * swith to Threading::For instead of raw OpenMP * apply review suggestions * apply review comments * remove device cpu
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- 24 May, 2022 1 commit
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Nikita Titov authored
* Update basic.py * Update test_engine.py * Add return type annotation
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- 24 Apr, 2022 1 commit
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Nikita Titov authored
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- 22 Apr, 2022 1 commit
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Miguel Trejo Marrufo authored
[python-package] remove 'fobj' in favor of passing custom objective function in params (fixes #3244) (#5052) * feat: support custom metrics in params * feat: support objective in params * test: custom objective and metric * fix: imports are incorrectly sorted * feat: convert eval metrics str and set to list * feat: convert single callable eval_metric to list * test: single callable objective in params Signed-off-by:
Miguel Trejo <armando.trejo.marrufo@gmail.com> * feat: callable fobj in basic cv function Signed-off-by:
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- 23 Mar, 2022 1 commit
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shiyu1994 authored
* new cuda framework * add histogram construction kernel * before removing multi-gpu * new cuda framework * tree learner cuda kernels * single tree framework ready * single tree training framework * remove comments * boosting with cuda * optimize for best split find * data split * move boosting into cuda * parallel synchronize best split point * merge split data kernels * before code refactor * use tasks instead of features as units for split finding * refactor cuda best split finder * fix configuration error with small leaves in data split * skip histogram construction of too small leaf * skip split finding of invalid leaves stop when no leaf to split * support row wise with CUDA * copy data for split by column * copy data from host to CPU by column for data partition * add synchronize best splits for one leaf from multiple blocks * partition dense row data * fix sync best split from task blocks * add support for sparse row wise for CUDA * remove useless code * add l2 regression objective * sparse multi value bin enabled for CUDA * fix cuda ranking objective * support for number of items <= 2048 per query * speedup histogram construction by interleaving global memory access * split optimization * add cuda tree predictor * remove comma * refactor objective and score updater * before use struct * use structure for split information * use structure for leaf splits * return CUDASplitInfo directly after finding best split * split with CUDATree directly * use cuda row data in cuda histogram constructor * clean src/treelearner/cuda * gather shared cuda device functions * put shared CUDA functions into header file * change smaller leaf from <= back to < for consistent result with CPU * add tree predictor * remove useless cuda_tree_predictor * predict on CUDA with pipeline * add global sort algorithms * add global argsort for queries with many items in ranking tasks * remove limitation of maximum number of items per query in ranking * add cuda metrics * fix CUDA AUC * remove debug code * add regression metrics * remove useless file * don't use mask in shuffle reduce * add more regression objectives * fix cuda mape loss add cuda xentropy loss * use template for different versions of BitonicArgSortDevice * add multiclass metrics * add ndcg metric * fix cross entropy objectives and metrics * fix cross entropy and ndcg metrics * add support for customized objective in CUDA * complete multiclass ova for CUDA * separate cuda tree learner * use shuffle based prefix sum * clean up cuda_algorithms.hpp * add copy subset on CUDA * add bagging for CUDA * clean up code * copy gradients from host to device * support bagging without using subset * add support of bagging with subset for CUDAColumnData * add support of bagging with subset for dense CUDARowData * refactor copy sparse subrow * use copy subset for column subset * add reset train data and reset config for CUDA tree learner add deconstructors for cuda tree learner * add USE_CUDA ifdef to cuda tree learner files * check that dataset doesn't contain CUDA tree learner * remove printf debug information * use full new cuda tree learner only when using single GPU * disable all CUDA code when using CPU version * recover main.cpp * add cpp files for multi value bins * update LightGBM.vcxproj * update LightGBM.vcxproj fix lint errors * fix lint errors * fix lint errors * update Makevars fix lint errors * fix the case with 0 feature and 0 bin fix split finding for invalid leaves create cuda column data when loaded from bin file * fix lint errors hide GetRowWiseData when cuda is not used * recover default device type to cpu * fix na_as_missing case fix cuda feature meta information * fix UpdateDataIndexToLeafIndexKernel * create CUDA trees when needed in CUDADataPartition::UpdateTrainScore * add refit by tree for cuda tree learner * fix test_refit in test_engine.py * create set of large bin partitions in CUDARowData * add histogram construction for columns with a large number of bins * add find best split for categorical features on CUDA * add bitvectors for categorical split * cuda data partition split for categorical features * fix split tree with categorical feature * fix categorical feature splits * refactor cuda_data_partition.cu with multi-level templates * refactor CUDABestSplitFinder by grouping task information into struct * pre-allocate space for vector split_find_tasks_ in CUDABestSplitFinder * fix misuse of reference * remove useless changes * add support for path smoothing * virtual destructor for LightGBM::Tree * fix overlapped cat threshold in best split infos * reset histogram pointers in data partition and spllit finder in ResetConfig * comment useless parameter * fix reverse case when na is missing and default bin is zero * fix mfb_is_na and mfb_is_zero and is_single_feature_column * remove debug log * fix cat_l2 when one-hot fix gradient copy when data subset is used * switch shared histogram size according to CUDA version * gpu_use_dp=true when cuda test * revert modification in config.h * fix setting of gpu_use_dp=true in .ci/test.sh * fix linter errors * fix linter error remove useless change * recover main.cpp * separate cuda_exp and cuda * fix ci bash scripts add description for cuda_exp * add USE_CUDA_EXP flag * switch off USE_CUDA_EXP * revert changes in python-packages * more careful separation for USE_CUDA_EXP * fix CUDARowData::DivideCUDAFeatureGroups fix set fields for cuda metadata * revert config.h * fix test settings for cuda experimental version * skip some tests due to unsupported features or differences in implementation details for CUDA Experimental version * fix lint issue by adding a blank line * fix lint errors by resorting imports * fix lint errors by resorting imports * fix lint errors by resorting imports * merge cuda.yml and cuda_exp.yml * update python version in cuda.yml * remove cuda_exp.yml * remove unrelated changes * fix compilation warnings fix cuda exp ci task name * recover task * use multi-level template in histogram construction check split only in debug mode * ignore NVCC related lines in parameter_generator.py * update job name for CUDA tests * apply review suggestions * Update .github/workflows/cuda.yml Co-authored-by:
Yu Shi <shiyu1994@qq.com> Co-authored-by:
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- 12 Mar, 2022 1 commit
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José Morales authored
[python-package] [R-package] propagate the best iteration of cvbooster into the individual boosters (#5066)
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- 09 Mar, 2022 1 commit
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shiyu1994 authored
* fix duplicate added initial scores for single-leaf trees * add test case * Fix import in Python test * commit python suggestions Co-authored-by:
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- 01 Mar, 2022 1 commit
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Nikita Titov authored
[tests][python] move tests that use `train()` function defined in `engine.py` from `test_basic.py` to `test_engine.py` (#5034) * Update test_basic.py * Update test_engine.py * Update test_engine.py
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- 24 Feb, 2022 1 commit
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José Morales authored
* map nullable dtypes to regular float dtypes * cast x3 to float after introducing missing values * add test for regular dtypes * use .astype and then values. update nullable_dtypes test and include test for regular numpy dtypes * more specific allowed dtypes. test no copy when single float dtype df * use np.find_common_type. set np.float128 to None when it isn't supported * set default as type(None) * move tests that use lgb.train to test_engine * include np.float32 when finding common dtype * Apply suggestions from code review Co-authored-by:
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- 15 Feb, 2022 1 commit
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José Morales authored
* make record_evaluation compatible with cv * test multiple metrics in cv * lint * fix cv with train metric. save stdv as well * always add dataset prefix to cv_agg * remove unused function
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- 12 Feb, 2022 1 commit
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Nikita Titov authored
* Update test_dask.py * Update test_engine.py * Update test_sklearn.py * Update test_sklearn.py * Update test_sklearn.py * Update test_sklearn.py * Update test_sklearn.py * Update test_sklearn.py * Update test_engine.py * Update test_sklearn.py * Update test_sklearn.py * Update test_sklearn.py
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