зеркало из https://github.com/microsoft/LightGBM.git
6b56a90cd1
* 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: Nikita Titov <nekit94-08@mail.ru> * Update .github/workflows/cuda.yml Co-authored-by: Nikita Titov <nekit94-08@mail.ru> * update header * remove useless TODOs * remove [TODO(shiyu1994): constrain the split with min_data_in_group] and record in #5062 * #include <LightGBM/utils/log.h> for USE_CUDA_EXP only * fix include order * fix include order * remove extra space * address review comments * add warning when cuda_exp is used together with deterministic * add comment about gpu_use_dp in .ci/test.sh * revert changing order of included headers Co-authored-by: Yu Shi <shiyu1994@qq.com> Co-authored-by: Nikita Titov <nekit94-08@mail.ru> |
||
|---|---|---|
| .. | ||
| README.md | ||
| append_comment.sh | ||
| get_workflow_status.py | ||
| install_opencl.ps1 | ||
| lint_r_code.R | ||
| rerun_workflow.sh | ||
| run_rhub_solaris_checks.R | ||
| set_commit_status.sh | ||
| setup.sh | ||
| test.sh | ||
| test_r_package.sh | ||
| test_r_package_solaris.sh | ||
| test_r_package_valgrind.sh | ||
| test_r_package_windows.ps1 | ||
| test_windows.ps1 | ||
| trigger_dispatch_run.sh | ||
README.md
Helper Scripts for CI
This folder contains scripts which are run on CI services.
Dockerfile used on CI service is maintained in a separate GitHub repository and can be pulled from Docker Hub.