Variant NNUE trainer

This is the chess variant NNUE training code for Fairy-Stockfish. See the documentation in the wiki for more details on the training process and join our discord to ask questions. This project is derived from the trainer for standard chess used for official Stockfish.

Setup

Requires a CUDA capable GPU. Note: you don't need to download the CUDA Toolkit

Package dependencies

At least Python 3.9 needed.

python3 -m venv env
source env/bin/activate
pip install -r requirements.txt

PyTorch with CUDA 11.8 will be automatically installed, along with the matching CuPy version If your GPU is CUDA 12.8 capable you can use requirements-CUDA128.txt instead of requirements.txt

Build the fast DataLoader

This requires a C++17 compiler and cmake.

Windows:

compile_data_loader.bat

Linux/Mac:

sh compile_data_loader.bat

Train a network

source env/bin/activate
python train.py train_data.bin val_data.bin

Resuming from a checkpoint

python train.py --resume_from_checkpoint <path> ...

Training on GPU

python train.py --gpus 1 ...

Feature set selection

By default the trainer uses a factorized HalfKAv2 feature set (named "HalfKAv2^") If you wish to change the feature set used then you can use the --features=NAME option. For the list of available features see --help The default is:

python train.py ... --features="HalfKAv2^"

Logging

pip install tensorboard
tensorboard --logdir=logs

Then, go to http://localhost:6006/