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)
