GitLab

Co-authored-by: Atanas Dimitrov <nasko119@abv.bg>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* add bagging by query for lambdarank

* fix pre-commit

* fix bagging by query with cuda

* fix bagging by query test case

* fix bagging by query test case

* fix bagging by query test case

* add #include <vector>

* Update include/LightGBM/objective_function.h
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

---------
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [python-package] Allow to pass early stopping min delta in params

* Fix test

* Add separate test

* Fix

* Add to cpp config

* Adjust test

* Adjust test

* Debug

* Revert

* Apply suggestions from code review

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

* [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 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: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_engine.py

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

* Update tests/python_package_test/test_engine.py

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

* Update tests/python_package_test/test_engine.py

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

* Update tests/python_package_test/test_engine.py

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

* Update tests/python_package_test/test_engine.py

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

* Update src/boosting/sample_strategy.cpp

modify warning about setting goss as `boosting_type`
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_engine.py

replace load_boston() with make_regression()

remove value checks of mean_squared_error in test_sample_strategy_with_boosting()

* Update tests/python_package_test/test_engine.py

add value checks of mean_squared_error in test_sample_strategy_with_boosting()

* Modify warnning about using goss as boosting type

* Update tests/python_package_test/test_engine.py

add random_state=42 for make_regression()

reduce the threshold of mean_square_error

* Update src/boosting/sample_strategy.cpp
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* remove goss from boosting types in documentation

* Update src/boosting/bagging.hpp
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update src/boosting/bagging.hpp
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update src/boosting/goss.hpp
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update src/boosting/goss.hpp
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* rename GOSS with GOSSStrategy

* update doc

* address comments

* fix table in doc

* Update include/LightGBM/config.h
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* update documentation

* update test case

* revert useless change in test_engine.py

* add tests for evaluation results in test_sample_strategy_with_boosting

* include <string>

* change to assert_allclose in test_goss_boosting_and_strategy_equivalent

* more tolerance in result checking, due to minor difference in results of gpu versions

* change == to np.testing.assert_allclose

* fix test case

* set gpu_use_dp to true

* change --report to --report-level for rstcheck

* use gpu_use_dp=true in test_goss_boosting_and_strategy_equivalent

* revert unexpected changes of non-ascii characters

* revert unexpected changes of non-ascii characters

* remove useless changes

* allocate gradients_pointer_ and hessians_pointer when necessary

* add spaces

* remove redundant virtual

* include <LightGBM/utils/log.h> for USE_CUDA

* check for  in test_goss_boosting_and_strategy_equivalent

* check for identity in test_sample_strategy_with_boosting

* remove cuda  option in test_sample_strategy_with_boosting

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update tests/python_package_test/test_engine.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* ResetGradientBuffers after ResetSampleConfig

* ResetGradientBuffers after ResetSampleConfig

* ResetGradientBuffers after bagging

* remove useless code

* check objective_function_ instead of gradients

* enable rf with goss

simplify params in test cases

* remove useless changes

* allow rf with feature subsampling alone

* change position of ResetGradientBuffers

* check for dask

* add parameter types for data_sample_strategy
Co-authored-by: Guangda Liu <v-guangdaliu@microsoft.com>
Co-authored-by: Yu Shi <shiyu_k1994@qq.com>
Co-authored-by: GuangdaLiu <90019144+GuangdaLiu@users.noreply.github.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* 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

* add binary objective for cuda_exp

* include <string> and <vector>

* exchange include ordering

* fix length of score to copy in evaluation

* fix EvalOneMetric

* fix cuda binary objective and prediction when boosting on gpu

* Add white space

* fix BoostFromScore for CUDABinaryLogloss

update log in test_register_logger

* include <algorithm>

* simplify shared memory buffer

* fix cuda_exp ci

* fix ci failures introduced by #5279

* cleanup cuda.yml

* fix test.sh

* clean up test.sh

* clean up test.sh

* skip lines by cuda_exp in test_register_logger

* Update tests/python_package_test/test_utilities.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* initial work for boosting and evaluation with CUDA

* fix compatibility with CPU code

* fix creating objective without USE_CUDA_EXP

* fix static analysis errors

* fix static analysis errors

* 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>

* fix duplicate added initial scores for single-leaf trees

* add test case

* Fix import in Python test

* commit python suggestions
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* add customized parser support

* fix typo of parser_config_file description

* make delimiter as parameter of JoinedLines

* 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 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

* [R-package] Remove CLI-only objects

* more guards

* more guards

* variable not string

* simplify fix

* revert build_r.R changes

* move define of global_timer
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update gbdt.cpp

* Update gbdt.cpp

* Apply suggestions from code review

* 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>

* [python] add start_iteration to python predict interface (#3058)

* Apply suggestions from code review

* Update lightgbm_R.h

* Apply suggestions from code review

* Apply suggestions from code review

* fix R interface

* update R documentation
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* feature importance type in saved model file

* fix nullptr

* fixed formatting

* fix python/R

* Update src/c_api.cpp

* Apply suggestions from code review
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* fix c_api test

* fix swig

* minor docs improvements and added defines for importance types
Co-authored-by: StrikerRUS <nekit94-12@hotmail.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* adding sparse support to TreeSHAP in lightgbm

* updating based on comments

* updated based on comments, used fromiter instead of frombuffer

* updated based on comments

* fixed limits import order

* fix sparse feature contribs to work with more than int32 max rows

* really fixed int64 max error and build warnings

* added sparse test with >int32 max rows

* fixed python side reshape check on sparse data

* updated based on latest comments

* fixed comments

* added CSC INT32_MAX validation to test, fixed comments

* 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.

* indent and constructor

* fix more

* fix long
Co-authored-by: StrikerRUS <nekit94-12@hotmail.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

* 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

* removed unused includes

* fixed index

* fix bagging

* fixed cpplint issues

* updated docs
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* fixed cpplint issues

* fixed cpplint issues

* 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