GitLab

* 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>

* [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>

This reverts commit 656d2676.

* [R-package] move R source files into R-package

* fix linting warning

* stuff

* [swig] Fix SWIG methods that return char** with StringArray.

+ [new] Add StringArray class to manage and manipulate arrays of fixed-length strings:

  This class is now used to wrap any char** parameters, manage memory and
  manipulate the strings.

  Such class is defined at swig/StringArray.hpp and wrapped in StringArray.i.

+ [API+fix] Wrap LGBM_BoosterGetFeatureNames it resulted in segfault before:

  Added wrapper LGBM_BoosterGetFeatureNamesSWIG(BoosterHandle) that
  only receives the booster handle and figures how much memory to allocate
  for strings and returns a StringArray which can be easily converted to String[].

+ [API+safety] For consistency, LGBM_BoosterGetEvalNamesSWIG was wrapped as well:

  * Refactor to detect any kind of errors and removed all the parameters
    besides the BoosterHandle (much simpler API to use in Java).
  * No assumptions are made about the required string space necessary (128 before).
  * The amount of required string memory is computed internally

+ [safety] No possibility of undefined behaviour

  The two methods wrapped above now compute the necessary string storage space
  prior to allocation, as the low-level C API calls would crash the process
  irreversibly if they write more memory than which is passed to them.

* Changes to C API and wrappers support char**

To support the latest SWIG changes that enable proper char**
return support that is safe, the C API was changed.

The respecive wrappers in R and Python were changed too.

* Cleanup indentation in new lightgbm_R.cpp code

* Adress review code-style comments.

* Update swig/StringArray.hpp
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

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

* Update src/lightgbm_R.cpp
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: alberto.ferreira <alberto.ferreira@feedzai.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [R-package] cleaned up formatting in R C/C++ files

* reverted some indentation changes

* fixed spacing for comments

* lightgbm to LightGBM

* fixed cpplint errors

* fixed more cpplint errors

* 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

* 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

* Update test values

* 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

* Update src/c_api.cpp
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Update src/io/tree.cpp
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Update src/io/tree.cpp
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Update tests/python_package_test/test_basic.py
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Remoove imports
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>

* added all necessary includes - fixed build/include_what_you_use error

* fixed the order of includes (build/include_order)

* 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 start_iteration in model saving

* fix test

* shuffle models ability

* fix bug

* update document

* refine

* Update engine.py

* Update basic.py

* fix comments

* fix comment

* fix include

* reduce dependency on header file

* fix build

* decode error description

* added break line char in log massages

* added code to expose c_api_pred_contrib in the R package

* removed Rprintf

* reverted to previous version of install.libs.R

* use int64 for string

* [R] Fatal when CSC exceed int32.max

* fix r random crash problem.

* fix R error msg.

* 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

* fix multi-threading.

* fix name style.

* support in CLI version.

* remove warnings.

* Not default parameters.

* fix if...else... .

* fix bug.

* fix warning.

* refine c_api.

* fix R-package.

* fix R's warning.

* fix tests.

* fix pep8 .

* Update lgb.Booster.R

Added method to call LGBM_BoosterLoadModelFromString_R if model_str is provided for initialization, added option to load from model_str in lgb.load

* Update lightgbm_R.cpp

Adding LGBM_BoosterLoadModelFromString_R

* Update lightgbm_R.cpp

Added LGBM_BoosterSaveModelToString_R

* Update lightgbm_R.cpp

* Update lgb.Booster.R

Added save_model_to_string method

* Update lgb.Booster.R

Implemented @Laurae2 comments

* Update lgb.Booster.R

* Update lightgbm_R.h

Added load and save model from/to string exports

* Added possibility to compile without openmp (useful for clang on Mac)

* Added CMake option to create dylib on MacOS

* finish R's c_api

* clean code

* fix sizeof pointer in 32bit system.

* add predictor class

* add Dataset class

* format code

* add booster

* add type check for expose function

* add a simple callback

* add all callbacks

* finish the basic training logic

* update docs

* add an simple training interface

* add basic test

* adapt the changes in c_api

* add test for Dataset

* add test for custom obj/eval functions

* fix python test

* fix bug in metadata init

* fix R CMD check