GitLab

* dev

* dev

* dev

* dev

* dev

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

* dev

* dev

* dev

* Update static_analysis.yml

* Update .pre-commit-config.yaml

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

[ci][docs] fix link checking action by switching from linkchecker to lychee and update some links (#7027)

Instead of replacing all #ifdef USE_CUDA, just add USE_CUDA define to ROCm build.

Previously #6086 added ROCm support but after numerous rebases it lost
critical changes. This PR restores the ROCm build.

There are many source file changes but most were automated using the
following:

```bash
for f in `grep -rl '#ifdef USE_CUDA'`
do
    sed -i 's@#ifdef USE_CUDA@#if defined(USE_CUDA) || defined(USE_ROCM)@g' $f
done

for f in `grep -rl '#endif  // USE_CUDA'`
do
    sed -i 's@#endif  // USE_CUDA@#endif  // USE_CUDA || USE_ROCM@g' $f
done
```

* [ci] [c++] use 'pre-commit' to run 'cpplint', upgrade to 'cpplint' 2.0.2

* remove bashisms

* one more pipefail use

* another pipefail

* [ROCm] add support for ROCm/HIP

- CMakeLists.txt ROCm updates, also replace glob with explicit file list
- initial warpSize interop changes
- helpers/hipify.sh script added
- .gitignore to ignore generated hip source files

* more rocm updates

- disable compiler warnings
- move PercentileDevice __device__ template function into header
- bug fixes for __host__ __define__ and __HIP__ preprocessor symbols

* more bug fixes

* warp 32 vs 64 updates

* lint fixes

* missing device_index variable

* accidental inclusion of hip headers

* copyright notice compliance

* Update CMakeLists.txt
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* fix lint issue

* clean up

* Update CMakeLists.txt
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update CMakeLists.txt
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* clean up CMakeLists.txt

use WARPSIZE

* use WARPSIZE

* fix share buffer size

---------
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Yu Shi <yushi2@microsoft.com>

* remove src/treelearner/kernels

* Update CMakeLists.txt

* clean up

* Update append-comment.sh

* Update static_analysis.yml

* Update static_analysis.yml

* Update basic.py

* Update basic.py

* Update .pre-commit-config.yaml

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update pyproject.toml

* Update pyproject.toml

* Update pyproject.toml

* Update pyproject.toml

* Update interactive_plot_example.ipynb

* Update pyproject.toml

* Update append-comment.sh

* Update basic.py

* Update basic.py

* Update pyproject.toml

* Update .pre-commit-config.yaml

* Update basic.py

* Update basic.py

* Update test_basic.R

* Update rank_objective.hpp

* Update histogram_16_64_256.cu

* Update static_analysis.yml

* ensure alphabetical order of rules

Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

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

* basic gpu_linear_tree_learner implementation

* corresponding config of gpu linear tree

* Update src/io/config.cpp
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* work around for gpu linear tree learner without gpu enabled

* add #endif

* add #ifdef USE_GPU

* fix lint problems

* fix compilation when USE_GPU is OFF

* add destructor

* add gpu_linear_tree_learner.cpp in make file list

* use template for linear tree learner

---------
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

Co-authored-by: Atanas Dimitrov <nasko119@abv.bg>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* support quantized training with categorical features on cpu

* remove white spaces

* add tests for quantized training with categorical features

* skip tests for cuda version

* fix cases when only 1 data block in row-wise quantized histogram construction with 8 inner bits

* remove useless capture

* fix compilation warnings

revert useless changes

* revert useless change

* separate functions in feature histogram into cpp file

* add feature_histogram.o in Makevars

* solve 'bin size 257 cannot run on GPU #3339'

https://github.com/microsoft/LightGBM/issues/3339#issuecomment-1665131743



* fix  typo LeafIndex -> leaf_index

---------
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

factor out uses of omp_get_num_threads() and omp_get_max_threads() outside of OpenMP wrapper (#6133)

* add quantized training (first stage)

* add histogram construction functions for integer gradients

* add stochastic rounding

* update docs

* fix compilation errors by adding template instantiations

* update files for compilation

* fix compilation of gpu version

* initialize gradient discretizer before share states

* add a test case for quantized training

* add quantized training for data distributed training

* Delete origin.pred

* Delete ifelse.pred

* Delete LightGBM_model.txt

* remove useless changes

* fix lint error

* remove debug loggings

* fix mismatch of vector and allocator types

* remove changes in main.cpp

* fix bugs with uninitialized gradient discretizer

* initialize ordered gradients in gradient discretizer

* disable quantized training with gpu and cuda

fix msvc compilation errors and warnings

* fix bug in data parallel tree learner

* make quantized training test deterministic

* make quantized training in test case more accurate

* refactor test_quantized_training

* fix leaf splits initialization with quantized training

* check distributed quantized training result

* add cuda gradient discretizer

* add quantized training for CUDA version in tree learner

* remove cuda computability 6.1 and 6.2

* fix parts of gpu quantized training errors and warnings

* fix build-python.sh to install locally built version

* fix memory access bugs

* fix lint errors

* mark cuda quantized training on cuda with categorical features as unsupported

* rename cuda_utils.h to cuda_utils.hu

* enable quantized training with cuda

* fix cuda quantized training with sparse row data

* allow using global memory buffer in histogram construction with cuda quantized training

* recover build-python.sh

enlarge allowed package size to 100M

* fix leaf splits update after split in quantized training

* fix preparation ordered gradients for quantized training

* remove force_row_wise in distributed test for quantized training

* Update src/treelearner/leaf_splits.hpp

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

* add quantized training (first stage)

* add histogram construction functions for integer gradients

* add stochastic rounding

* update docs

* fix compilation errors by adding template instantiations

* update files for compilation

* fix compilation of gpu version

* initialize gradient discretizer before share states

* add a test case for quantized training

* add quantized training for data distributed training

* Delete origin.pred

* Delete ifelse.pred

* Delete LightGBM_model.txt

* remove useless changes

* fix lint error

* remove debug loggings

* fix mismatch of vector and allocator types

* remove changes in main.cpp

* fix bugs with uninitialized gradient discretizer

* initialize ordered gradients in gradient discretizer

* disable quantized training with gpu and cuda

fix msvc compilation errors and warnings

* fix bug in data parallel tree learner

* make quantized training test deterministic

* make quantized training in test case more accurate

* refactor test_quantized_training

* fix leaf splits initialization with quantized training

* check distributed quantized training result

Fix for DEBUG mode

This commit fixes issue #5777

* [ci] speed up if-else, swig, and lint conda setup

* add 'source activate'

* python constraint

* start removing cuda v1

* comment out CI

* remove more references

* revert some unnecessaary changes

* revert a few more mistakes

* revert another change that ignored params

* sigh

* remove CUDATreeLearner

* fix tests, docs

* fix quoting in setup.py

* restore all CI

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

* Apply suggestions from code review

* completely remove cuda_exp, update docs

---------
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

remove redundant whitespaces

* add feature interaction constraint for cuda_exp

* test feature interaction constraints for cuda_exp

* remove useless check

* update comment

* add huber regression for cuda_exp

* renew tree output on GPU

add test cases for regression objectives

* remove useless changes

* add white space

* fix test_regression

* fix cuda_exp ci

* fix ci failures introduced by #5279

* cleanup cuda.yml

* fix test.sh

* clean up test.sh

* clean up test.sh

* skip lines by cuda_exp in test_register_logger

* Update tests/python_package_test/test_utilities.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Fix potential overflow in linear trees

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

* initial work for boosting and evaluation with CUDA

* fix compatibility with CPU code

* fix creating objective without USE_CUDA_EXP

* fix static analysis errors

* fix static analysis errors

Clear split info buffer in cost efficient gradient boosting before every iteration (fix partially #3679) (#5164)

* clear split info buffer in cegb_ before every iteration

* check nullable of cegb_ in serial_tree_learner.cpp

* add a test case for checking the split buffer in CEGB

* swith to Threading::For instead of raw OpenMP

* apply review suggestions

* apply review comments

* remove device cpu