GitLab

* move all submodules to external_libs folder

* Update .Rbuildignore

* Update MANIFEST.in

* Update .appveyor.yml

* Update CMakeLists.txt

* Update build_r.R

* Update test.sh

* Update setup.py

* Update CMakeLists.txt

* Update test.sh

* Update setup.py

* Update conf.py

* Update MANIFEST.in

* Update LightGBM.vcxproj

* continue

* test

* test

* Update setup.py

* hotfix

* revert CI tests

* [python-package] remove unused Eigen files (fixes #3684)

* more changes

* add EIGEN_MPL2_ONLY in VS solution file

* fix VS project

* remove EIGEN_MPL2_ONLY define in linear_tree_learner
Co-authored-by: Nikita Titov <nekit94-12@hotmail.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

* 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 int64 write error

* attempt

* [WIP] [ci] [R-package] Add CI job that runs valgrind tests

* update all-successful

* install

* executable

* fix redirect stuff

* Apply suggestions from code review
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* more flags

* add mc to msvc proj

* fix memory leak in mc

* Update monotone_constraints.hpp

* Update r_package.yml

* remove R_INT64_PTR

* disable openmp

* Update gbdt_model_text.cpp

* Update gbdt_model_text.cpp

* Apply suggestions from code review

* try to free vector

* free more memories.

* Update src/boosting/gbdt_model_text.cpp

* fix using

* try the UNPROTECT(1);

* fix a const pointer

* fix Common

* reduce UNPROTECT

* remove UNPROTECT(1);

* fix null handle

* fix predictor

* use NULL after free

* fix a leaking in test

* try more fixes

* test the effect of tests

* throw exception in Fatal

* add test back

* Apply suggestions from code review

* commet some tests

* Apply suggestions from code review

* Apply suggestions from code review

* trying to comment out tests

* Update openmp_wrapper.h

* Apply suggestions from code review

* Update configure

* Update configure.ac

* trying to uncomment

* more comments

* more uncommenting

* more uncommenting

* fix comment

* more uncommenting

* uncomment fully-commented out stuff

* try uncommenting more dataset tests

* uncommenting more tests

* ok getting closer

* more uncommenting

* free dataset

* skipping a test, more uncommenting

* more skipping

* re-enable OpenMP

* allow on OpenMP thing

* move valgrind to comment-only job

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

* changes from code review

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

* linting

* issue comments too

* remove issue_comment
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Add capability to get possible max and min values for a model

* Change implementation to have return value in tree.cpp, change naming to upper and lower bound, move implementation to gdbt.cpp

* Update include/LightGBM/c_api.h
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Change iteration to avoid potential overflow, add bindings to R and Python and a basic test

* Adjust test values

* Consider const correctness and multithreading protection

* Put everything possible as const

* Include shared_mutex, for now as unique_lock

* Update test values

* Put everything possible as const

* Include shared_mutex, for now as unique_lock

* Make PredictSingleRow const and share the lock with other reading threads

* Update test values

* Add test to check that model is exactly the same in all platforms

* Try to parse the model to get the expected values

* Try to parse the model to get the expected values

* Fix implementation, num_leaves can be lower than the leaf_value_ size

* Do not check for num_leaves to be smaller than actual size and get back to test with hardcoded value

* Change test order

* Add gpu_use_dp option in test

* Remove helper test method

* Remove TODO

* Add preprocessing option to compile with c++17

* Update python-package/setup.py
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Remove unwanted changes

* Move option

* Fix problems introduced by conflict fix

* Avoid switching to c++17 and use yamc mutex library to access shared lock functionality

* Add extra yamc include

* Change header order

* some lint fix

* change include order and remove some extra blank lines

* Further fix lint issues

* Update c_api.cpp

* Further fix lint issues

* Move yamc include files to a new yamc folder

* Use standard unique_lock

* Update windows/LightGBM.vcxproj
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* Update windows/LightGBM.vcxproj.filters
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* Update windows/LightGBM.vcxproj.filters
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update windows/LightGBM.vcxproj.filters
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update windows/LightGBM.vcxproj.filters
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Fix problems coming from merge conflict resolution
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: joanfontanals <jfontanals@ntent.com>
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* Update LightGBM.vcxproj

* Update LightGBM.vcxproj.filters

* commit

* fix msvc

* fix format

* 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

* add debug mode in camke

* add debug dll

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

* fix naming

* Apply suggestions from code review

* Apply suggestions from code review

* Update LightGBM.sln

* refine

* run MPI job in debug mode

* document USE_DEBUG and USE_TIMETAG
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* code refactoring

* update vcproject

* refine

* fix test

* Update tests/python_package_test/test_sklearn.py

* fix test

* add Link Time Code Generation

* remove ltcg

* Apply suggestions from code review

* 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>

* Implementation of XE_NDCG loss function for ranking.

* Add citation

* Check in example usage for xe_ndcg loss.

* Seed the generator when a seed is provided in the config. Add unit-tests for xe_ndcg

* Update documentation

* Fix indentation

* Address issues raised by reviewers.

* Clean up include statements.

* Fix issues raised by reviewers.

* Regenerate parameters.rst

* Add a note to explain that reproducing xe_ndcg results requires num_threads to be one.

* Introduce objective_seed and use that in rank_xendcg instead of directly using seed

* Change default value of objective_seed

* 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 travis badge

* updated GitHub Microsoft URL

* [WIP] refine config

* [wip] ready for the auto code generate

* auto generate config codes

* use with to open file

* fix bug

* fix pylint

* fix bug

* fix pylint

* fix bugs.

* tmp for failed test.

* fix tests.

* added nthreads alias

* added new aliases from new config.h

* fixed duplicated alias

* refactored parameter_generator.py

* added new aliases from config.h and removed remaining old names

* fix bugs & some miss alias

* added aliases

* add more descriptions.

* add comment.

* [optional] support protobuf

* fix windows/LightGBM.vcxproj

* add doc

* fix doc

* fix vs support (#2)

* fix vs support

* fix cmake

This reverts commit 53b99854.

* add R's library file to vs project and cmake.

* support using dll built by vs.

* better search for the library file.

* remove mingw related doc .

* update document.

* Let R handle the library compile.

* try fix build from github.

* Update README.md

* cleaner build.

* fix the install problem in linux.

* Update README.md

* Add early stopping for prediction

* Fix GBDT if-else prediction with early stopping

* Small C++ embelishments to early stopping API and functions

* Fix early stopping efficiency issue by creating a singleton for no early stopping

* Python improvements to early stopping API

* Add assertion check for binary and multiclass prediction score length

* Update vcxproj and vcxproj.filters with new early stopping files

* Remove inline from PredictRaw(), the linker was not able to find it otherwise

* Revert "python-package: support valid_names in scikit-learn API (#420)"

This reverts commit de39dbcf.

* Revert "faster histogram sum up (#418)"

This reverts commit 98c7c2a3.

* some refactor.

* two stage sum up to reduce sum up error.

* add more two-stage sumup.

* some refactor.

* add alignment.

* change name to aligned_allocator.

* remove some useless sumup.

* fix a warning.

* add -march=native .

* remove the padding of gradients.

* no alignment.

* fix test.

* change KNumSumupGroup to 32768.

* change gcc flags.

* many refactors.

* remove multi_loglossova.

* fix tests.

* avoid using lambda function.

* fix some format.

* reduce branching.