def test_optimise():
from cchess_alphazero.worker.optimize import start
from cchess_alphazero.config import Config
from cchess_alphazero.lib.logger import setup_logger
c = Config('mini')
c.resource.create_directories()
setup_logger(c.resource.main_log_path)
start(c)
def setup(config: Config, args):
config.opts.new = args.new
if args.total_step is not None:
config.trainer.start_total_steps = args.total_step
config.opts.device_list = args.gpu
config.resource.create_directories()
if args.cmd == 'self':
setup_logger(config.resource.main_log_path)
elif args.cmd == 'opt':
setup_logger(config.resource.opt_log_path)
elif args.cmd == 'play' or args.cmd == 'ob':
setup_logger(config.resource.play_log_path)
elif args.cmd == 'eval':
setup_logger(config.resource.eval_log_path)
elif args.cmd == 'sl':
setup_logger(config.resource.sl_log_path)
def setup(config: Config, args):
config.opts.new = args.new
if args.total_step is not None:
config.trainer.start_total_steps = args.total_step
config.opts.device_list = args.gpu
config.resource.create_directories()
if args.cmd == 'self':
setup_logger(config.resource.main_log_path)
elif args.cmd == 'opt':
setup_logger(config.resource.opt_log_path)
elif args.cmd == 'play' or args.cmd == 'ob':
setup_logger(config.resource.play_log_path)
elif args.cmd == 'eval':
setup_logger(config.resource.eval_log_path)
elif args.cmd == 'sl':
setup_logger(config.resource.sl_log_path)
def setup(config: Config, args):
config.opts.new = args.new
if args.total_step is not None:
config.trainer.start_total_steps = args.total_step
config.resource.create_directories()
if args.cmd == 'self':
setup_logger(config.resource.main_log_path)
elif args.cmd == 'self2':
setup_logger(config.resource.main_log_path)
elif args.cmd == 'opt':
setup_logger(config.resource.opt_log_path)
elif args.cmd == 'play':
setup_logger(config.resource.play_log_path)
from cchess_alphazero.play_games import play
def setup_parameters(config):
num_cores = mp.cpu_count()
search_threads = 10 if num_cores < 10 else (num_cores // 10) * 10
print(f"search_threads = {search_threads}")
config.play.search_threads = search_threads
if __name__ == "__main__":
mp.freeze_support()
sys.setrecursionlimit(10000)
config_type = 'distribute'
config = Config(config_type=config_type)
config.opts.device_list = '0'
config.resource.create_directories()
setup_logger(config.resource.play_log_path)
config.opts.new = False
config.opts.light = False
pwhc = PlayWithHumanConfig()
pwhc.update_play_config(config.play)
config.opts.bg_style = 'WOOD'
setup_parameters(config)
simulation_num = input('请输入AI搜索次数（必须为整数）：')
ai_move_first = input('AI执红？(Y/N)')
ai_move_first = True if ai_move_first == 'Y' or ai_move_first == 'y' else False
config.play.simulation_num_per_move = int(simulation_num)
play.start(config, not ai_move_first)
input('按任意键退出...')
def setup_parameters(config):
if len(sys.argv) > 1:
config.internet.username = sys.argv[1]
print(f'用户名设置为：{config.internet.username}')
num_cores = mp.cpu_count()
max_processes = 2
if len(sys.argv) > 2:
max_processes = int(sys.argv[2])
search_threads = 20
print(
f"max_processes = {max_processes}, search_threads = {search_threads}")
config.play.max_processes = max_processes
config.play.search_threads = search_threads
if __name__ == "__main__":
sys.setrecursionlimit(10000)
config_type = 'distribute'
config = Config(config_type=config_type)
config.opts.device_list = '0'
config.resource.create_directories()
setup_logger(config.resource.main_log_path)
config.internet.distributed = False
config.opts.log_move = True
config.opts.has_history = True
setup_parameters(config)
# config.internet.download_url = 'http://alphazero-1251776088.cossh.myqcloud.com/model/128x7/model_best_weight.h5'
self_play.start(config)
if len(sys.argv) > 2:
flag = sys.argv[2]
if flag == 'new':
config.internet.base_url = 'http://temp.52coding.com.cn'
elif flag == 'new2':
config.internet.base_url = 'http://temp3.52coding.com.cn'
config.internet.upload_url = f'{config.internet.base_url}/api/upload_game_file/192x10'
config.internet.upload_eval_url = f'{config.internet.base_url}/api/upload_eval_game_file'
config.internet.get_latest_digest = f'{config.internet.base_url}/api/get_latest_digest/192x10'
config.internet.get_evaluate_model_url = f'{config.internet.base_url}/api/query_for_evaluate'
config.internet.update_elo_url = f'{config.internet.base_url}/api/add_eval_result/'
search_threads = 20
print(
f"max_processes = {max_processes}, search_threads = {search_threads}")
config.play.max_processes = max_processes
config.play.search_threads = search_threads
if __name__ == "__main__":
sys.setrecursionlimit(10000)
config_type = 'distribute'
config = Config(config_type=config_type)
config.opts.device_list = '0'
config.opts.log_move = True
config.resource.create_directories()
setup_logger(config.resource.eval_log_path)
config.eval.update_play_config(config.play)
setup_parameters(config)
# config.internet.download_base_url = 'http://alphazero-1251776088.cossh.myqcloud.com/model/'
evaluator.start(config)
def setup_parameters(config):
num_cores = mp.cpu_count()
search_threads = 10 if num_cores < 10 else 20
print(f"search_threads = {search_threads}")
config.play.search_threads = search_threads
if __name__ == "__main__":
mp.freeze_support()
sys.setrecursionlimit(10000)
config_type = 'distribute'
config = Config(config_type=config_type)
config.opts.device_list = '0'
config.resource.create_directories()
setup_logger(config.resource.play_log_path)
config.opts.new = False
config.opts.light = False
pwhc = PlayWithHumanConfig()
pwhc.update_play_config(config.play)
config.opts.bg_style = 'WOOD'
setup_parameters(config)
simulation_num = input('请输入AI搜索次数（必须为整数）：')
ai_move_first = input('AI执红？(Y/N)')
ai_move_first = True if ai_move_first == 'Y' or ai_move_first == 'y' else False
config.play.simulation_num_per_move = int(simulation_num)
play.start(config, not ai_move_first)
input('按任意键退出...')