def decide_simulation_num_per_move(self, idx):
ret = read_as_int(self.config.resource.force_simulation_num_file)
if ret:
logger.debug(f"loaded simulation num from file: {ret}")
return ret
for min_idx, num in self.config.play.schedule_of_simulation_num_per_move:
if idx >= min_idx:
ret = num
return ret
def start(config: Config):
tf_util.set_session_config(per_process_gpu_memory_fraction=0.3)
api_server = MultiProcessReversiModelAPIServer(config)
process_num = config.play_data.multi_process_num
api_server.start_serve()
with Manager() as manager:
shared_var = SharedVar(
manager,
game_idx=read_as_int(config.resource.self_play_game_idx_file) or 0)
with ProcessPoolExecutor(max_workers=process_num) as executor:
futures = []
for i in range(process_num):
play_worker = SelfPlayWorker(config,
env=ReversiEnv(),
api=api_server.get_api_client(),
shared_var=shared_var,
worker_index=i)
futures.append(executor.submit(play_worker.start))
def start(config: Config):
tf_util.set_session_config(allow_growth=True)
# api_server_list = [MultiProcessReversiModelAPIServer(config) for i in range(config.model.num_gpus)]
api_server = MultiProcessReversiModelAPIServer(config)
api_server.start_serve()
process_num = config.play_data.multi_process_num
# for i in range(config.model.num_gpus):
# api_server_list[i].start_serve(i)
# print(f'Create server on GPU#{i}')
with Manager() as manager:
shared_var = SharedVar(
manager,
game_idx=read_as_int(config.resource.self_play_game_idx_file) or 0)
with ProcessPoolExecutor(max_workers=process_num) as executor:
futures = []
for i in range(process_num):
play_worker = SelfPlayWorker(config,
env=ReversiEnv(),
api=api_server.get_api_client(),
shared_var=shared_var,
worker_index=i)
futures.append(executor.submit(play_worker.start))