GitLab

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

[python-package] do not copy column-major numpy arrays when creating Dataset from list of arrays (#6773)
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* 1) Fixed Predictor lifecycle
2) Fixed Boosting trees initialization

#5482

* Added tests for LGBM_BoosterPredictForMat in Contrib mode

* #6778 Reverted indentation to 4 spaces

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

[R-package] [c++] add tighter multithreading control, avoid global OpenMP side effects (fixes #4705, fixes #5102) (#6226)

* Add serialization of reference dataset

* lint and missing file

* Fixes from reviewers

* responded to comments

* revert sdk change

* Extract streaming to own PR

* small merge fixes and cleanup

* linting fixes

* fix cast warning

* Fix accidental deletion during branch transfer

* responded to initial triage comments

* Added more tests to use create-from-samples APIs

* added mutex and adjusted nclasses logic

* Fix thread-safety for pushing data to sparse bins through Push APIs

* lint and doc fixes

* Small SWIG fix

* nit fix

* Responded to StrikerRUS comments

* fix breaking change after merge with master

* Extract streaming to own PR

* small merge fixes and cleanup

* Fix accidental deletion during branch transfer

* responded to initial triage comments

* Added more tests to use create-from-samples APIs

* Fix rstcheck call in ci

* remove TODOs

* Extract streaming to own PR

* small merge fixes and cleanup

* Fix accidental deletion during branch transfer

* responded to initial triage comments

* Added more tests to use create-from-samples APIs

* Small SWIG fix

* remove ci change

* responded to shiyu1994 comments

* responded to StrikerRUS comments

* Fixes from StrikerRUS comments

* Adjust LGBM_DatasetCreateFromSampledColumn to handle distributed data better

* linting fix

* switch to 1 API with breaking change

* Fix pything native call

* more python test fixes

* check feature names and order in predict with dataframe

* slice df in predict to remove the target

* scramble features

* handle int column names

* only change column order when needed

* include validate_features param in booster and sklearn estimators

* document validate_features argument

* use all_close in preds checks and check for assertion error to compare different arrays

* perform remapping and checks in cpp

* remove extra logs

* fixes

* revert cpp

* proposal

* remove extra arg

* lint

* restore _data_from_pandas arguments

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

* move data conversion to Predictor.predict

* use Vector2Ptr
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* check number of features when retrieving number of bins

* check for negative values

* lint

* expose FeatureNumBin in C api

* parametrize min_data_in_bin and add test with max_bin_by_feature

* include feature_num_bin in R package

* add suggestion from review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* update error message and lint

* lint

* add call method

* minor improvements in tests

* add suggestions from review

* lint

* rename argument to feature in python and r packages
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* add C API function that returns all param names with aliases

* add C API function that returns all param names with aliases

* add R code

* test R code

* remove debug CI

* fix R lint

* refactor

* run CI

* fix R

* fix

* revert CI checks

* revert changes in docs

* Try to make function `const`
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* add `const` in cpp file

* address review comments and sync with `master`
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* [c_api] Improve ANSI compatibility by avoiding <stdbool.h>

* fixes in response to CI linting

* inline NOLINT instead of separate test

* moving length declaration to non-ANSI C conditional

* [c_api] Align expected return type in `basic.py` with new c_api type.

* mock func for no openmp

* use omp_get_max_threads
Co-authored-by: hzy46 <email@example.com>

This removes code duplication for creating sample indices.

* [python-package] create Dataset from sampled data.

* [python-package] create Dataset from List[Sequence].

1. Use random access for data sampling
2. Support read data from multiple input files
3. Read data in batch so no need to hold all data in memory

* [python-package] example: create Dataset from multiple HDF5 file.

* fix: revert is_class implementation for seq

* fix: unwanted memory view reference for seq

* fix: seq is_class accepts sklearn matrices

* fix: requirements for example

* fix: pycode

* feat: print static code linting stage

* fix: linting: avoid shell str regex conversion

* code style: doc style

* code style: isort

* fix ci dependency: h5py on windows

* [py] remove rm files in test seq
https://github.com/microsoft/LightGBM/pull/4089#discussion_r612929623

* docs(python): init_from_sample summary

https://github.com/microsoft/LightGBM/pull/4089#discussion_r612903389



* remove dataset dump sample data debugging code.

* remove typo fix.

Create separate PR for this.

* fix typo in src/c_api.cpp
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* style(linting): py3 type hint for seq

* test(basic): os.path style path handling

* Revert "feat: print static code linting stage"

This reverts commit 10bd79f7f8258bea8e61c3abb8c9c7e4456a916d.

* feat(python): sequence on validation set

* minor(python): comment

* minor(python): test option hint

* style(python): fix code linting

* style(python): add pydoc for ref_dataset

* doc(python): sequence
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

* revert(python): sequence class abc

* chore(python): remove rm_files

* Remove useless static_assert.

* refactor: test_basic test for sequence.

* fix lint complaint.

* remove dataset._dump_text in sequence test.

* Fix reverting typo fix.

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

* Fix type hint, code and doc style.

* fix failing test_basic.

* Remove TODO about keep constant in sync with cpp.

* Install h5py only when running python-examples.

* Fix lint complaint.

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

* Doc fixes, remove unused params_str in __init_from_seqs.

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

* Remove unnecessary conda install in windows ci script.

* Keep param as example in dataset_from_multi_hdf5.py

* Add _get_sample_count function to remove code duplication.

* Use batch_size parameter in generate_hdf.

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

* Fix after applying suggestions.

* Fix test, check idx is instance of numbers.Integral.

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

* Expose Sequence class in Python-API doc.

* Handle Sequence object not having batch_size.

* Fix isort lint complaint.

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

* Update docstring to mention Sequence as data input.

* Remove get_one_line in test_basic.py

* Make Sequence an abstract class.

* Reduce number of tests for test_sequence.

* Add c_api: LGBM_SampleCount, fix potential bug in LGBMSampleIndices.

* empty commit to trigger ci

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

* Rename to LGBM_GetSampleCount, change LGBM_SampleIndices out_len to int32_t.

Also rename total_nrow to num_total_row in c_api.h for consistency.

* Doc about Sequence in docs/Python-Intro.rst.

* Fix: basic.py change LGBM_SampleIndices out_len to int32.

* Add create_valid test case with Dataset from Sequence.

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

* Apply suggestions from code review
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

* Remove no longer used DEFAULT_BIN_CONSTRUCT_SAMPLE_CNT.

* Update python-package/lightgbm/basic.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Willian Zhang <willian@willian.email>
Co-authored-by: Willian Z <Willian@Willian-Zhang.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* New build option: USE_PRECISE_TEXT_PARSER.

Use fast_double_parser for text file parsing. For each number, fallback
to strtod in case of parse failure.

* Add benchmark for CSVParser with Atof and AtofPrecise.

* Fix lint complaint.

* Fix typo in open result error message.

* Revert "Fix lint complaint."

This reverts commit 92ab0b6bce9f17d7be9eaeb20f19d4a0a36f0387.

* Revert "Add benchmark for CSVParser with Atof and AtofPrecise."

This reverts commit 4f8639abd06c679d4382eb715a1793afd94df3d2.

* Use AtofPrecise in Common::__StringToTHelper.

* [option] precise_float_parser: precise float number parsing for text input.

* Remove USE_PRECISE_TEXT_PARSER compile option.

* test: add test for Common::AtofPrecise.

* test: remove ChunkedArrayTest with 0 length.

This triggers Log::Fatal which aborts the test program.

* fix lint, add copyright.

* Revert "test: remove ChunkedArrayTest with 0 length."

This reverts commit 346c76affe9e78b6ca2738c4a56dbb9c00f31102.

* Use LightGBM::Common::Sign

* save precise_float_parser in model file.

* Fix error checking in AtofPrecise. Add more test cases.

* Remove test case that can't pass under macOS.

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

* Fix index out-of-range exception generated by BaggingHelper on small datasets.

Prior to this change, the line "score_t threshold = tmp_gradients[top_k - 1];" would generate an exception, since tmp_gradients would be empty when the cnt input value to the function is zero.

* Update goss.hpp

* Update goss.hpp

* Add API method LGBM_BoosterPredictForMats which runs prediction on a data set given as of array of pointers to rows (as opposed to existing method LGBM_BoosterPredictForMat which requires data given as contiguous array)

* Fix incorrect upstream merge

* Add link to LightGBM.NET

* Fix indenting to 2 spaces

* Dummy edit to trigger CI

* Dummy edit to trigger CI

* remove duplicate functions from merge

* Fix for CreatePredictor function: for VS2017 in Debug build, the previous version would end up giving an uninitialised prediction function that would throw access violation exceptions when invoked.
Co-authored-by: matthew-peacock <matthew.peacock@whiteoakam.com>
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

By using a unique lock instead of the shared lock the timings are very similar,
but predictions are correct.

Even so, by designing a small C++ benchmark with a very simple LGBM model,more threads on a simple model are slower than
the single-thread case. This is probably due to very small work units,
the lock contention overhead increases.

We should in the future benchmark with more complex models to see if supporting
threading on these calls is worth it in performance gains.

If not, then we could choose to not to provide thread-safety and remove
the locks altogether for maximal throughput.

See https://github.com/microsoft/LightGBM/issues/3751 for timings.

See gist for benchmark code:

  https://gist.github.com/AlbertoEAF/5972db15a27c294bab65b97e1bc4c315

* Cleanup predictor

* Cleanup SingleRowPredictor

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

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

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

* [R-package] allow access to params in Booster

* remove unnecessary whitespace

* fix test on resetting params

* remove pytest_cache

* Update R-package/tests/testthat/test_custom_objective.R

* small code and docs refactoring

* Update CMakeLists.txt

* Update .vsts-ci.yml

* Update test.sh

* continue

* continue

* revert stable sort for all-unique values

* 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

* Refactor c_api.cpp with template code

* Further cleanup

* Fix whitespace for linter

* 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

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* 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>