a5cd2412de
* Create pyproject.toml * Implement a custom build backend (see below) in packager directory. Build logic from setup.py has been refactored and migrated into the new backend. * Tested: pip wheel . (build wheel), python -m build --sdist . (source distribution)
824 B
824 B
XGBoost Plugin for Federated Learning
This folder contains the plugin for federated learning. Follow these steps to build and test it.
Install gRPC
Refer to the installation guide from the gRPC website.
Build the Plugin
# Under xgboost source tree.
mkdir build
cd build
cmake .. -GNinja \
-DPLUGIN_FEDERATED=ON \
-DUSE_CUDA=ON\
-DUSE_NCCL=ON
ninja
cd ../python-package
pip install -e .
If CMake fails to locate gRPC, you may need to pass -DCMAKE_PREFIX_PATH=<grpc path> to CMake.
Test Federated XGBoost
# Under xgboost source tree.
cd tests/distributed
# This tests both CPU training (`hist`) and GPU training (`gpu_hist`).
./runtests-federated.sh