Visit p3achyjr.github.io/p3achygo-page for more details about methods, implementation, and current status.
Assuming inside docker container [docs tbd], run the following commands.
mkdir /tmp/p3achygo
mkdir /tmp/shuffler
./sh/build_all_container.sh
To run a single process that iteratively runs self-play, trains, and runs eval, do
python -m python.rl_loop.train_sp_eval --sp_bin_path=/app/bazel-bin/cc/selfplay/main --eval_bin_path=/app/bazel-bin/cc/eval/main --run_id=${RUN_ID} 2>&1 | tee /tmp/sp_log.txt
To run the shuffler, do
python -m python.rl_loop.shuffle --bin_path=/app/bazel-bin/cc/shuffler/main --run_id=${RUN_ID} --local_run_dir=/tmp/shuffler
Alternatively, you can run the CC binaries themselves. For eval, do
./bazel-bin/cc/eval/main --cur_model_path=${CUR_MODEL_PATH} --cand_model_path=${CAND_MODEL_PATH} --num_games=${NUM_GAMES} --cache_size=${CACHE_SIZE} --cur_n=${CUR_N} --cur_k=${CUR_K} --cand_n=${CAND_N} --cand_k=${CAND_K}