trader_cli = RLTraderCLI() args = trader_cli.get_args() rewards = { "incremental-profit": IncrementalProfit, "weighted-unrealized-profit": WeightedUnrealizedProfit } reward_strategy = rewards[args.reward_strat] if __name__ == '__main__': logger = init_logger(__name__, show_debug=args.debug) from lib.RLTrader import RLTrader trader = RLTrader(**vars(args), logger=logger, reward_strategy=reward_strategy) if args.command == 'train': trader.train(n_epochs=args.epochs, save_every=args.save_every, test_trained_model=args.test_trained, render_test_env=args.render_test, render_report=args.render_report, save_report=args.save_report) elif args.command == 'test': trader.test(model_epoch=args.model_epoch, render_env=args.render_env, render_report=args.render_report, save_report=args.save_report) elif args.command == 'update-static-data': download_data_async()
import numpy as np from lib.RLTrader import RLTrader from lib.TraderArgs import TraderArgs from lib.util.logger import init_logger np.warnings.filterwarnings('ignore') option_parser = TraderArgs() args = option_parser.get_args() if __name__ == '__main__': logger = init_logger(__name__, show_debug=args.debug) trader = RLTrader(**vars(args), logger=logger) if args.command == 'optimize': trader.optimize(n_trials=args.trials, n_parallel_jobs=args.parallel_jobs) elif args.command == 'train': trader.train(n_epochs=args.epochs) elif args.command == 'test': trader.test(model_epoch=args.model_epoch, should_render=args.no_render) elif args.command == 'opt-train-test': trader.optimize(args.trials, args.parallel_jobs) trader.train(n_epochs=args.train_epochs, test_trained_model=args.no_test, render_trained_model=args.no_render)
import multiprocessing from lib.RLTrader import RLTrader np.warnings.filterwarnings('ignore') def optimize_code(params): trader = RLTrader(**params) trader.optimize() if __name__ == '__main__': n_process = multiprocessing.cpu_count() params = {'n_cpu': n_process} # processes = [] # for i in range(n_process): # processes.append(multiprocessing.Process(target=optimize_code, args=(params,))) # for p in processes: # p.start() # for p in processes: # p.join() trader = RLTrader(**params) # trader.train(test_trained_model=True, render_trained_model=True) trader.test(model_epoch=10)