def main(): log.info('Loading %s...', Game.__name__) g = Game(4, 9, 4) log.info('Loading %s...', nn.__name__) nnet = nn(g) if args.load_model: log.info('Loading checkpoint "%s/%s"...', args.load_folder_file[0], args.load_folder_file[1]) nnet.load_checkpoint(args.load_folder_file[0], args.load_folder_file[1]) else: log.warning('Not loading a checkpoint!') log.info('Loading the Coach...') c = Coach(g, nnet, args) if args.load_model: log.info("Loading 'trainExamples' from file...") c.loadTrainExamples() log.info('Starting the learning process 🎉') c.learn()
'--load_model', dest='load_model', action='store_true') parser.add_argument('-loadf', '--load_folder_file', dest='load_folder_file', type=str) parser.add_argument('-iterexamp', '--num_iters_example', dest='numItersForTrainExamplesHistory', type=int, default=20) args = parser.parse_args() fh = open(os.path.join("..", "data", "puzzle1.txt")) fcontent = fh.read() fh.close() sys.setrecursionlimit(10000) g = game(fcontent) nnet = nn(g, args) if args.load_model: nnet.load_checkpoint(args.load_folder_file) c = Coach(g, nnet, args) if args.load_model: print("Load trainExamples from file") c.loadTrainExamples() c.learn()
dropout_rate=configs.dropout_rate, epochs=configs.num_epochs, batch_size=configs.batch_size, num_channels=configs.num_channels, log_device_placement=configs.log_device_placement, network_architecture=configs.network_architecture) coach = Coach(game=game, nnet=nnet, pnet=pnet, num_iters=configs.num_iters, root_noise=configs.root_noise, board_size=configs.board_size) if configs.load_model: logging.info("Loading training examples") coach.loadTrainExamples() if configs.web_server: web = WebServer(game=game, nnet=nnet, checkpoint_folder=configs.checkpoint_dir, c_puct=configs.c_puct, num_mcst_sims=configs.num_mcts_sims) web.start_web_server() exit(0) coach.learn(num_train_episodes=configs.num_episodes, num_training_examples_to_keep=configs.maxlenOfQueue, checkpoint_folder=configs.checkpoint_dir, arena_tournament_size=configs.arena_size, model_update__win_threshold=configs.update_threshold,