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* 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 param name

* Update gpu_tree_learner.h

* Update gbdt.h

* 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 test for interaction constraints and monotone constraints

* enforce interaction constraints in RecomputeBestSplitForLeaf

* code formatting

* code formatting

* move interaction constraint test to test_engine

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

* clarify DEBUG-level log about tree depth

* more places

* Add check to prevent out of index lookup in the position discount table. Add debug logging to report number of queries found in the data.

* Change debug logging location so that we can print the data file name as well.

* Revert "Change debug logging location so that we can print the data file name as well."

This reverts commit 3981b34bd6e0530f89c4733e78e6b6603bf50d48.

* Add data file name to debug logging.

* Move log line to a place where it is output even when query IDs are read from a separate file.

* Also add the out-of-range check to rank metrics.

* Perform check after number of queries is initialized.

* Update

* Update docs to note that pred_contrib is not available for linear trees

* Add warning in code

* Change warning to error

* 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 evalution of linear trees with a single leaf.

Note that trees without linear models at the leaf always handle num_leaves = 1 as a special case and directly output the leaf value.  Linear trees were missing this special case handling, and hence would have the following issues:
 * Calling Tree::Predict or Tree::PredictByMap would cause an access violation exception attempting to access the first value of the empty split_feature_ array in GetLeaf.
 * PredictionFunLinear would either cause an access violation or go into an infinite loop when attempting to do the equivalent of GetLeaf.

Note also that PredictionFun does not need the same changes as PredictionFunLinear, since both are only called by Tree::AddPredictionToScore, which has a special case for (!is_linear_ && num_leaves_ <= 1) that precludes calling PredictionFun.
Co-authored-by: matthew-peacock <matthew.peacock@whiteoakam.com>
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

Use high precision conversion from double to string in Tree::ToString() for new linear tree members (#3938)

* 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

* In Tree::ToString() method, print double values for linear tree models with high precision, so that the tree may be accurately reproduced elsewhere (LightGBM.Net in particular)

* Need to use more precise StringToArray instead of StringToArrayFast when parsing double valued arrays for linear trees, to ensure models round-trip via string or file correctly.
Co-authored-by: matthew-peacock <matthew.peacock@whiteoakam.com>
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* [docs] Change some 'parallel learning' references to 'distributed learning'

* found a few more

* one more reference

* 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>

* remove unused private field

* mask Train as override

* remove unused private field

* Add new task type: "save_binary".

* Document for task "save_binary".

* Update test_utilities.py

* Update cuda.yml

* Update test_utilities.py

* Update cuda_tree_learner.cpp

* Update cuda.yml

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] enable use of trees with linear models at leaves (fixes #3319)

* remove problematic pragmas

* fix tests

* try to fix build scripts

* try fixing pragma check

* more pragma checks

* ok fix pragma stuff for real

* empty commit

* regenerate documentation

* try skipping test

* uncomment CI

* add note on missing value types for R

* add tests on saving and re-loading booster

* Update cuda_tree_learner.cpp

* Update cuda_tree_learner.h

* Update cuda.yml

Co-authored-by: jingwei.su <jingwei.su@hulu.com>

* Fix compiler warnings caused by implicit type conversion

* Fix more warnings

* Fix more warnings

* Fix monotone constraint bug where split does not fulfill constraints.

* Fix indent.