GitLab

Compile warnings have been fixed

* 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>

* 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>

Co-authored-by: Ubuntu <shiyu@gbdt-shiyu.ren3kv4wanvufliwrpy4k03lsf.xx.internal.cloudapp.net>

This reverts commit 656d2676.

* Support UTF-8 characters in feature name again

This commit reverts 0d59859c.
Also see:
- https://github.com/microsoft/LightGBM/issues/2226
- https://github.com/microsoft/LightGBM/issues/2478
- https://github.com/microsoft/LightGBM/pull/2229

I reproduced the issue and as @kidotaka gave us a great survey in #2226,
I don't conclude that the cause is UTF-8, but "an empty string (character)".
Therefore, I revert "throw error when meet non ascii (#2229)" whose commit hash
is 0d59859c, and add support feture names as UTF-8 again.

* add tests

* fix check-docs tests

* update

* fix tests

* update .travis.yml

* fix tests

* update test_r_package.sh

* update test_r_package.sh

* update test_r_package.sh

* add a test for R-package

* update test_r_package.sh

* update test_r_package.sh

* update test_r_package.sh

* fix test for R-package

* update test_r_package.sh

* update test_r_package.sh

* update test_r_package.sh

* update test_r_package.sh

* update

* updte

* update

* remove unneeded comments

* fixed cpplint errors and disable warning only for VS

* wrap more pragma warning

* commit

* fix msvc

* fix format

* speed up for const hessian

* rename template

* fix clang build

* template init

* add comment

* reduce overhead of get num_threads

* add warning

* Apply suggestions from code review

* Apply suggestions from code review

* 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>

* added feature infos to JSON dump

* slight json schema refactor

* simpified code

* refactor feature_infos

* refactoring

* Update src/boosting/gbdt.cpp

* Update dataset.h

* Update include/LightGBM/dataset.h

* simplify

* Apply suggestions from code review

* parse string and construct JSON objs
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* remove related cpp codes

* removed more mentiones of init_score_filename params
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* reset

* fix a bug

* fix test

* Update c_api.h

* support to no filter features by min_data

* add warning in reset config

* refine warnings for override dataset's parameter

* some cleans

* clean code

* clean code

* refine C API function doxygen comments

* refined new param description

* refined doxygen comments for R API function

* removed stuff related to int8

* break long line in warning message

* removed tests which results cannot be validated anymore

* added test for warnings about unchangeable params

* write parameter from dataset to booster

* consider free_raw_data.

* fix params

* fix bug

* implementing R

* fix typo

* filter params in R

* fix R

* not min_data

* refined tests

* fixed linting

* refine

* pilint

* add docstring

* fix docstring

* R lint

* updated description for C API function

* use param aliases in Python

* fixed typo

* fixed typo

* added more params to test

* removed debug print

* fix dataset construct place

* fix merge bug

* Update feature_histogram.hpp

* add is_sparse back

* remove unused parameters

* fix lint

* add data random seed

* update

* [R-package] centrallized Dataset parameter aliases and added tests on Dataset parameter updating (#2767)
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* commit

* refactoring

* Update src/io/bin.cpp

* Apply suggestions from code review

* bug

* code clean

* remove warning

* commit

* update parameter

* 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>

* implement

* fix warning

* fix bug

* fix a bug

* remove unneed function

* fix data push bug

* fix valid data push

* fix bug for missing_type=zero

* refine split

* renames

* typo

* fix predict with header

* avoid duplicated feature names

* reduce the buffer when using high dimensional data in distributed mode.

* Update dataset_loader.cpp

* refix

* typo

* fix number of bin accumulation.

* avoid overflow

* fix warning

* efficient solution.

* Update dataset.h

* fix bin count output

* fix warning

* bug in dist number of feature check

* fix possible edge case

* Update dataset.cpp

* possible bug fix

* fix

* fixed miscellaneous typos in documentation

* fix typo introduced in typo-fixing PR

* check the shape for mat, csr and csc

* guess from csr

* support file checking

* better error msg

* grammar

* clean code

* code clean

* check range for CSR

* Update test_.py

* Update test_.py

* added tests

* Fix bug where small values of max_bin cause crash.

* Revert "Fix bug where small values of max_bin cause crash."

This reverts commit fe5c8e2547057c1fa5750bcddd359dd7708fab4b.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Change binning behavior to be same as PR #2342.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Change binning behavior to be same as PR #2342.

* Add functionality to force bin thresholds.

* Fix style issues.

* Minor style and doc fixes.

* Add functionality to force bin thresholds.

* Fix style issues.

* Minor style and doc fixes.

* Change binning behavior to be same as PR #2342.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Change binning behavior to be same as PR #2342.

* Use different bin finding function for predefined bounds.

* Fix style issues.

* Minor refactoring, overload FindBinWithZeroAsOneBin.

* Fix style issues.

* Fix bug and add new test.

* Add warning when using categorical features with forced bins.

* Pass forced_upper_bounds by reference.

* Pass container types by const reference.

* Get categorical features using FeatureBinMapper.

* Fix bug for small max_bin.

* Move GetForcedBins to DatasetLoader.

* Find forced bins in dataset_loader.

* Minor fixes.

* fix many cpp lint errors

* indent

* fix bug

* fix more

* fix gpu

* more fixes

* throw error when meet non ascii

* check ascii for config strings.

* Add parameter max_bin_by_feature.

* Fix minor bug.

* Fix minor bug.

* Fix calculation of header size for writing binary file.

* Fix style issues.

* Fix python style issue.

* Fix test and python style issue.

* added all necessary includes - fixed build/include_what_you_use error

* fixed the order of includes (build/include_order)

* Initial attempt to implement appending features in-memory to another data set

The intent is for this to enable munging files together easily, without needing to round-trip via numpy or write multiple copies to disk.
In turn, that enables working more efficiently with data sets that were written separately.

* Implement Dataset.dump_text, and fix small bug in appending of group bin boundaries.

Dumping to text enables us to compare results, without having to worry about issues like features being reordered.

* Add basic tests for validation logic for add_features_from.

* Remove various internal mapping items from dataset text dumps

These are too sensitive to the exact feature order chosen, which is not visible to the user.
Including them in tests appears unnecessary, as the data dumping code should provide enough coverage.

* Add test that add_features_from results in identical data sets according to dump_text.

* Add test that booster behaviour after using add_features_from matches that of training on the full data

This checks:
- That training after add_features_from works at all
- That add_features_from does not cause training to misbehave

* Expose feature_penalty and monotone_types/constraints via get_field

These getters allow us to check that add_features_from does the right thing with these vectors.

* Add tests that add_features correctly handles feature_penalty and monotone_constraints.

* Ensure add_features_from properly frees the added dataset and add unit test for this

Since add_features_from moves the feature group pointers from the added dataset to the dataset being added to, the added dataset is invalid after the call.
We must ensure we do not try and access this handle.

* Remove some obsolete TODOs

* Tidy up DumpTextFile by using a single iterator for each feature

This iterators were also passed around as raw pointers without being freed, which is now fixed.

* Factor out offsetting logic in AddFeaturesFrom

* Remove obsolete TODO

* Remove another TODO

This one is debatable, test code can be a bit messy and duplicate-heavy, factoring it out tends to end badly.
Leaving this for now, will revisit if adding more tests later on becomes a mess.

* Add documentation for newly-added methods.

* Fix whitespace issues identified by pylint.

* Fix a few more whitespace issues.

* Fix doc comments

* Implement deep copying for feature groups.

* Replace awkward std::move usage by emplace_back, and reduce vector size to num_features rather than num_total_features.

* Copy feature groups in addFeaturesFrom, rather than moving them.

* Fix bugs in FeatureGroup copy constructor and ensure source dataset remains usable

* Add reserve to PushVector and PushOffset

* Move definition of Clone into class body

* Fix PR review issues

* Fix for loop increment style.

* Fix test failure

* Some more docstring fixes.

* Remove blank line

* add warnings for override parameters of Dataset

* fix pep8

* add feature_penalty

* refactor

* add R's code

* Update basic.py

* Update basic.py

* fix parameter bug

* Update lgb.Dataset.R

* fix a bug

* add per-feature-penalites

* fix comment

* [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.