GitLab

[python-package] Add support for NumPy 2.0, test against nightly versions of dependencies (fixes #6454) (#6467)

[R-package] skip integer categorical feature check when building dataset subset (fixes #6412) (#6442)

[ci] Skip Arrow tests on AppVeyor, use Intel macOS runners, upgrade to XCode 14.3 on macOS jobs, disable MacOS MPI jobs (#6425)

Co-authored-by: José Morales <jmoralz92@gmail.com>

* Update .vsts-ci.yml for Azure Pipelines

Upgrade Azure VM Scale Set to use Mariner (Azure Linux) systems.

* Update .vsts-ci.yml

* Update .vsts-ci.yml

* Update .vsts-ci.yml

* Update .vsts-ci.yml

* Update .vsts-ci.yml

* upgrade clang to clang-17

* add -y in apt install

* update name of mariner agent pool

* fix clang 17 compiler name

* apt update before install clang 17

* update libomp version for clang 17

* use clang-17 only for Mariner agents

* fix CXX and CC

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

* 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