GitLab

Previously #6086 added ROCm support but after numerous rebases it lost
critical changes. This PR restores the ROCm build.

There are many source file changes but most were automated using the
following:

```bash
for f in `grep -rl '#ifdef USE_CUDA'`
do
    sed -i 's@#ifdef USE_CUDA@#if defined(USE_CUDA) || defined(USE_ROCM)@g' $f
done

for f in `grep -rl '#endif  // USE_CUDA'`
do
    sed -i 's@#endif  // USE_CUDA@#endif  // USE_CUDA || USE_ROCM@g' $f
done
```

* fix leaf splits update after split in quantized training

* fix preparation ordered gradients for quantized training

* remove force_row_wise in distributed test for quantized training

* Update src/treelearner/leaf_splits.hpp

---------
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* 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

* [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: shiyu1994 <shiyu_k1994@qq.com>

* Apply suggestions from code review

* completely remove cuda_exp, update docs

---------
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

* 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

* 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>

* issue fix #4601

* fix issue 4601 it2

* add tests for issue 4601

* fix warning

* fix warning

* add new line at end

* remove last line at end

* fix lint warning

* address comments

* address comments

* address comments

* fix address

* address comments

* revert seed

* fix recursive force split issue

* fix build error

* fix lint warning

* Correct spelling

Most changes were in comments, and there were a few changes to literals for log output.

There were no changes to variable names, function names, IDs, or functionality.

* Clarify a phrase in a comment
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Clarify a phrase in a comment
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Clarify a phrase in a comment
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Correct spelling

Most are code comments, but one case is a literal in a logging message.

There are a few grammar fixes too.
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* add test for interaction constraints and monotone constraints

* enforce interaction constraints in RecomputeBestSplitForLeaf

* code formatting

* code formatting

* move interaction constraint test to test_engine

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Add Eigen library.

* Working for simple test.

* Apply changes to config params.

* Handle nan data.

* Update docs.

* Add test.

* Only load raw data if boosting=gbdt_linear

* Remove unneeded code.

* Minor updates.

* Update to work with sk-learn interface.

* Update to work with chunked datasets.

* Throw error if we try to create a Booster with an already-constructed dataset having incompatible parameters.

* Save raw data in binary dataset file.

* Update docs and fix parameter checking.

* Fix dataset loading.

* Add test for regularization.

* Fix bugs when saving and loading tree.

* Add test for load/save linear model.

* Remove unneeded code.

* Fix case where not enough leaf data for linear model.

* Simplify code.

* Speed up code.

* Speed up code.

* Simplify code.

* Speed up code.

* Fix bugs.

* Working version.

* Store feature data column-wise (not fully working yet).

* Fix bugs.

* Speed up.

* Speed up.

* Remove unneeded code.

* Small speedup.

* Speed up.

* Minor updates.

* Remove unneeded code.

* Fix bug.

* Fix bug.

* Speed up.

* Speed up.

* Simplify code.

* Remove unneeded code.

* Fix bug, add more tests.

* Fix bug and add test.

* Only store numerical features

* Fix bug and speed up using templates.

* Speed up prediction.

* Fix bug with regularisation

* Visual studio files.

* Working version

* Only check nans if necessary

* Store coeff matrix as an array.

* Align cache lines

* Align cache lines

* Preallocation coefficient calculation matrices

* Small speedups

* Small speedup

* Reverse cache alignment changes

* Change to dynamic schedule

* Update docs.

* Refactor so that linear tree learner is not a separate class.

* Add refit capability.

* Speed up

* Small speedups.

* Speed up add prediction to score.

* Fix bug

* Fix bug and speed up.

* Speed up dataload.

* Speed up dataload

* Use vectors instead of pointers

* Fix bug

* Add OMP exception handling.

* Change return type of LGBM_BoosterGetLinear to bool

* Change return type of LGBM_BoosterGetLinear back to int, only parameter type needed to change

* Remove unused internal_parent_ property of tree

* Remove unused parameter to CreateTreeLearner

* Remove reference to LinearTreeLearner

* Minor style issues

* Remove unneeded check

* Reverse temporary testing change

* Fix Visual Studio project files

* Restore LightGBM.vcxproj.filters

* Speed up

* Speed up

* Simplify code

* Update docs

* Simplify code

* Initialise storage space for max num threads

* Move Eigen to include directory and delete unused files

* Remove old files.

* Fix so it compiles with mingw

* Fix gpu tree learner

* Change AddPredictionToScore back to const

* Fix python lint error

* Fix C++ lint errors

* Change eigen to a submodule

* Update comment

* Add the eigen folder

* Try to fix build issues with eigen

* Remove eigen files

* Add eigen as submodule

* Fix include paths

* Exclude eigen files from Python linter

* Ignore eigen folders for pydocstyle

* Fix C++ linting errors

* Fix docs

* Fix docs

* Exclude eigen directories from doxygen

* Update manifest to include eigen

* Update build_r to include eigen files

* Fix compiler warnings

* Store raw feature data as float

* Use float for calculating linear coefficients

* Remove eigen directory from GLOB

* Don't compile linear model code when building R package

* Fix doxygen issue

* Fix lint issue

* Fix lint issue

* Remove uneeded code

* Restore delected lines

* Restore delected lines

* Change return type of has_raw to bool

* Update docs

* Rename some variables and functions for readability

* Make tree_learner parameter const in AddScore

* Fix style issues

* Pass vectors as const reference when setting tree properties

* Make temporary storage of serial_tree_learner mutable so we can make the object's methods const

* Remove get_raw_size, use num_numeric_features instead

* Fix typo

* Make contains_nan_ and any_nan_ properties immutable again

* Remove data_has_nan_ property of tree

* Remove temporary test code

* Make linear_tree a dataset param

* Fix lint error

* Make LinearTreeLearner a separate class

* Fix lint errors

* Fix lint error

* Add linear_tree_learner.o

* Simulate omp_get_max_threads if openmp is not available

* Update PushOneData to also store raw data.

* Cast size to int

* Fix bug in ReshapeRaw

* Speed up code with multithreading

* Use OMP_NUM_THREADS

* Speed up with multithreading

* Update to use ArrayToString

* Fix tests

* Fix test

* Fix bug introduced in merge

* Minor updates

* Update docs

* store without offset in multi_val_dense_bin

* fix offset bug

* add comment for offset

* add comment for bin type selection

* faster operations for offset

* keep most freq bin in histogram for multi val dense

* use original feature iterators

* consider 9 cases (3 x 3) for multi val bin construction

* fix dense bin setting

* fix bin data in multi val group

* fix offset of the first feature histogram

* use float hist buf

* avx in histogram construction

* use avx for hist construction without prefetch

* vectorize bin extraction

* use only 128 vec

* use avx2

* use vectorization for sparse row wise

* add bit size for multi val dense bin

* float with no vectorization

* change multithreading strategy to dynamic

* remove intrinsic header

* fix dense multi val col copy

* remove bit size

* use large enough block size when the bin number is large

* calc min block size by sparsity

* rescale gradients

* rollback gradients scaling

* single precision histogram buffer as an option

* add float hist buffer with thread buffer

* fix setting zero in hist data

* fix hist begin pointer in tree learners

* remove debug logs

* remove omp simd

* update Makevars of R-package

* fix feature group binary storing

* two row wise for double hist buffer

* add subfeature for two row wise

* remove useless code and fix two row wise

* refactor code

* grouping the dense feature groups can get sparse multi val bin

* clean format problems

* one thread for two blocks in sep row wise

* use ordered gradients for sep row wise

* fix grad ptr

* ordered grad with combined block for sep row wise

* fix block threading

* use the same min block size

* rollback share min block size

* remove logs

* Update src/io/dataset.cpp
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* fix parameter description

* remove sep_row_wise

* remove check codes

* add check for empty multi val bin

* fix lint error

* rollback changes in config.h

* Apply suggestions from code review
Co-authored-by: Ubuntu <shiyu@gbdt-04.ren3kv4wanvufliwrpy4k03lsf.xx.internal.cloudapp.net>
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* fix warnings

* Apply suggestions from code review

* Update feature_group.h

* Update feature_group.h

* Update src/treelearner/serial_tree_learner.cpp

* Update multiclass_metric.hpp

* Make path smoothing faster

* Fix bug

* Fix bug

* Minor style fix

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* Initial CUDA work

* redirect log to python console (#3090)

* redir log to python console

* fix pylint

* Apply suggestions from code review

* Update basic.py

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update c_api.h

* Apply suggestions from code review

* Apply suggestions from code review

* super-minor: better wording
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: StrikerRUS <nekit94-12@hotmail.com>

* re-order includes (fixes #3132) (#3133)

* Revert "re-order includes (fixes #3132) (#3133)" (#3153)

This reverts commit 656d2676

.

* Missing change from previous rebase

* Minor cleanup and removal of development scripts.

* Only set gpu_use_dp on by default for CUDA. Other minor change.

* Fix python lint indentation problem.

* More python lint issues.

* Big lint cleanup - more to come.

* Another large lint cleanup - more to come.

* Even more lint cleanup.

* Minor cleanup so less differences in code.

* Revert is_use_subset changes

* Another rebase from master to fix recent conflicts.

* More lint.

* Simple code cleanup - add & remove blank lines, revert unneccessary format changes, remove added dead code.

* Removed parameters added for CUDA and various bug fix.

* Yet more lint and unneccessary changes.

* Revert another change.

* Removal of unneccessary code.

* temporary appveyor.yml for building and testing

* Remove return value in ReSize

* Removal of unused variables.

* Code cleanup from reviewers suggestions.

* Removal of FIXME comments and unused defines.

* More reviewers comments cleanup.

* More reviewers comments cleanup.

* More reviewers comments cleanup.

* Fix config variables.

* Attempt to fix check-docs failure

* Update Paramster.rst for num_gpu

* Removing test appveyor.yml

* Add ƒCUDA_RESOLVE_DEVICE_SYMBOLS to libraries to fix linking issue.

* Fixed handling of data elements less than 2K.

* More reviewers comments cleanup.

* Removal of TODO and fix printing of int64_t

* Add cuda change for CI testing and remove cuda from device_type in python.

* Missed one change form previous check-in

* Removal AdditionConfig and fix settings.

* Limit number of GPUs to one for now in CUDA.

* Update Parameters.rst for previous check-in

* Whitespace removal.

* Cleanup unused code.

* Changed uint/ushort/ulong to unsigned int/short/long to help Windows based CUDA compiler work.

* Lint change from previous check-in.

* Changes based on reviewers comments.

* More reviewer comment changes.

* Adding warning for is_sparse. Revert tmp_subset code. Only return FeatureGroupData if not is_multi_val_

* Fix so that CUDA code will compile even if you enable the SCORE_T_USE_DOUBLE define.

* Reviewer comment cleanup.

* Replace warning with Log message. Removal of some of the USE_CUDA. Fix typo and removal of pragma once.

* Remove PRINT debug for CUDA code.

* Allow to use of multiple GPUs for CUDA.

* More multi-GPUs enablement for CUDA.

* More code cleanup based on reviews comments.

* Update docs with latest config changes.
Co-authored-by: Gordon Fossum <fossum@us.ibm.com>
Co-authored-by: ChipKerchner <ckerchne@linux.vnet.ibm.com>
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: StrikerRUS <nekit94-12@hotmail.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Add interaction constraints functionality.

* Minor fixes.

* Minor fixes.

* Change lambda to function.

* Fix gpu bug, remove extra blank lines.

* Fix gpu bug.

* Fix style issues.

* Try to fix segfault on MACOS.

* Fix bug.

* Fix bug.

* Fix bugs.

* Change parameter format for R.

* Fix R style issues.

* Change string formatting code.

* Change docs to say R package not supported.

* Remove R functionality, moving to separate PR.

* Keep track of branch features in tree object.

* Only track branch features when feature interactions are enabled.

* Fix lint error.

* Update docs and simplify tests.

This reverts commit 656d2676.

* Add util functions.

* Added monotone_constraints_method as a parameter.

* Add the intermediate constraining method.

* Updated tests.

* Minor fixes.

* Typo.

* Linting.

* Ran the parameter generator for the doc.

* Removed usage of the FeatureMonotone function.

* more fixes

* Fix.

* Remove duplicated code.

* Add debug checks.

* Typo.

* Bug fix.

* Disable the use of intermediate monotone constraints and feature sampling at the same time.

* Added an alias for monotone constraining method.

* Use the right variable to get the number of threads.

* Fix DEBUG checks.

* Add back check to determine if histogram is splittable.

* Added forgotten override keywords.

* Perform monotone constraint update only when necessary.

* Small refactor of FastLeafConstraints.

* Post rebase commit.

* Small refactor.

* Typo.

* Added comment and slightly improved logic of monotone constraints.

* Forgot a const.

* Vectors that are to be modified need to be pointers.

* Rename FastLeafConstraints to IntermediateLeafConstraints to match documentation.

* Remove overload of GoUpToFindLeavesToUpdate.

* Stop memory leaking.

* Fix cpplint issues.

* Fix checks.

* Fix more cpplint issues.

* Refactor config monotone constraints method.

* Typos.

* Remove useless empty lines.

* Add new line to separate includes.

* Replace unsigned ind by size_t.

* Reduce number of trials in tests to decrease CI time.

* Specify monotone constraints better in tests.

* Removed outer loop in test of monotone constraints.

* Added categorical features to the monotone constraints tests.

* Add blank line.

* Regenerate parameters automatically.

* Speed up ShouldKeepGoingLeftRight.
Co-authored-by: Charles Auguste <auguste@dubquantdev801.ire.susq.com>
Co-authored-by: guolinke <guolin.ke@outlook.com>

* speed up for const hessian

* rename template

* some refactorings

* refine

* refine

* simplify codes

* fix random in feature histogram

* code refine

* refine

* try fix

* make gcc happy

* remove timer

* rollback some changes

* more templates

* fix a bug

* reduce the cost of timer

* fix gpu

* fix bug

* fix gpu

* fixed cpplint errors

* fixed more cpplint errors

* refix

* fix config

* avoid to rely on config

* speed up multi-val bin subset for bagging

* remove the duplicated codes

* code refine

* some codes refactoring

* move `is_constant_hessian` into `TrainingShareStates`

* refine

* fix bug

* fix bug when num_groups_ < 0

* fix gpu

* fix gpu bagging

* fix gpu bug

* typo

* Update src/treelearner/serial_tree_learner.h

* don't cache `num_thread`, to avoid change outside

* rename

* update document

* Update docs/Parameters.rst

* Update include/LightGBM/config.h

* Apply suggestions from code review
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Apply suggestions from code review
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* some refines

* more omp refactoring

* format define

* fix merge bug

* some fixes

* fix some warnings

* Apply suggestions from code review

* Apply suggestions from code review

* remove dup codes

* commit

* refactoring

* Update src/io/bin.cpp

* Apply suggestions from code review

* bug

* code clean

* remove warning

* commit

* update parameter

* Move monotone constraints to the monotone_constraints files.

* Add checks for debug mode.

* Refactored FindBestSplitsFromHistograms.

* Add headers.

* fix

* Update data_parallel_tree_learner.cpp

* simplify ComputeBestSplitForFeature

* Fix min / max issue.

* Remove duplicated check.
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* various minor style, docs and cpplint improvements

* fixed typo in warning

* fix recently added cpplint errors

* move note for params upper in description for consistency

* commit

* fix a bug

* fix bug

* reset to track changes

* refine the auto choose logic

* sort the time stats output

* fix include

* change  multi_val_bin_sparse_threshold

* add cmake

* add _mm_malloc and _mm_free for cross platform

* fix cmake bug

* timer for split

* try to fix cmake

* fix tests

* refactor DataPartition::Split

* fix test

* typo

* formating

* Revert "formating"

This reverts commit 5b8de4f7fb9d975ee23701d276a66d40ee6d4222.

* add document

* [R-package] Added tests on use of force_col_wise and force_row_wise in training (#2719)

* naming

* fix gpu code

* Update include/LightGBM/bin.h
Co-Authored-By: James Lamb <jaylamb20@gmail.com>

* Update src/treelearner/ocl/histogram16.cl

* test: swap compilers for CI

* fix omp

* not avx2

* no aligned for feature histogram

* Revert "refactor DataPartition::Split"

This reverts commit 256e6d9641ade966a1f54da1752e998a1149b6f8.

* slightly refactor data partition

* reduce the memory cost
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* refactoring

* fix style

* fix style

* Update cost_effective_gradient_boosting.hpp

* Update serial_tree_learner.cpp

* Update serial_tree_learner.h

* fix style

* update vc project

* Update cost_effective_gradient_boosting.hpp

* fix many cpp lint errors

* indent

* fix bug

* fix more

* fix gpu

* more fixes

* update

* fix a bug

* Update config.h

* Update Parameters.rst

* add parameter

* implement

* fix bug

* fix bug

* fix according comment

* add test

* Update test_engine.py

* Update test_engine.py

* Update test_engine.py

* fix a bug when bagging with reset_config

* clean code

* added all necessary includes - fixed build/include_what_you_use error

* fixed the order of includes (build/include_order)

* Add configuration parameters for CEGB.

* Add skeleton CEGB tree learner

Like the original CEGB version, this inherits from SerialTreeLearner.
Currently, it changes nothing from the original.

* Track features used in CEGB tree learner.

* Pull CEGB tradeoff and coupled feature penalty from config.

* Implement finding best splits for CEGB

This is heavily based on the serial version, but just adds using the coupled penalties.

* Set proper defaults for cegb parameters.

* Ensure sanity checks don't switch off CEGB.

* Implement per-data-point feature penalties in CEGB.

* Implement split penalty and remove unused parameters.

* Merge changes from CEGB tree learner into serial tree learner

* Represent features_used_in_data by a bitset, to reduce the memory overhead of CEGB, and add sanity checks for the lengths of the penalty vectors.

* Fix bug where CEGB would incorrectly penalise a previously used feature

The tree learner did not update the gains of previously computed leaf splits when splitting a leaf elsewhere in the tree.
This caused it to prefer new features due to incorrectly penalising splitting on previously used features.

* Document CEGB parameters and add them to the appropriate section.

* Remove leftover reference to cegb tree learner.

* Remove outdated diff.

* Fix warnings

* Fix minor issues identified by @StrikerRUS.

* Add docs section on CEGB, including citation.

* Fix link.

* Fix CI failure.

* Add some unit tests

* Fix pylint issues.

* Fix remaining pylint issue