def main(): parser = argparse.ArgumentParser() parser.add_argument('--bind-address', default='127.0.0.1') parser.add_argument('--port', '-p', type=int, default=5000) parser.add_argument('--pg-agent') parser.add_argument('--predict-agent') parser.add_argument('--q-agent') parser.add_argument('--ac-agent') args = parser.parse_args() bots = {'mcts': mcts.MCTSAgent(800, temperature=0.7)} if args.pg_agent: bots['pg'] = agent.load_policy_agent(h5py.File(args.pg_agent)) if args.predict_agent: bots['predict'] = agent.load_prediction_agent( h5py.File(args.predict_agent)) if args.q_agent: q_bot = rl.load_q_agent(h5py.File(args.q_agent)) q_bot.set_temperature(0.01) bots['q'] = q_bot if args.ac_agent: ac_bot = rl.load_ac_agent(h5py.File(args.ac_agent)) ac_bot.set_temperature(0.05) bots['ac'] = ac_bot web_app = httpfrontend.get_web_app(bots) web_app.run(host=args.bind_address, port=args.port, threaded=False)
def main(): workdir = '//home/nail//Code_Go//checkpoints//' os.chdir(workdir) bind_address = '127.0.0.1' port = 5000 predict_agent, pg_agent, q_agent, ac_agent = '', '', '', '' agent_type = input('Агент(pg/predict/q/ac = ').lower() if agent_type == 'pg': pg_agent = input( 'Введите имя файла для игры с ботом политика градиентов =') pg_agent = workdir + pg_agent + '.h5' if agent_type == 'predict': predict_agent = input( 'Введите имя файла для игры с ботом предсказания хода =') predict_agent = workdir + predict_agent + '.h5' if agent_type == 'q': q_agent = input( 'Введите имя файла для игры с ботом ценность действия =') q_agent = workdir + q_agent + '.h5' if agent_type == 'ac': ac_agent = input('Введите имя файла для игры с ботом актор-критик =') ac_agent = workdir + ac_agent + '.h5' bots = {'mcts': mcts.MCTSAgent(800, temperature=0.7)} if agent_type == 'pg': bots['pg'] = agent.load_policy_agent(h5py.File(pg_agent, 'r')) if agent_type == 'predict': bots['predict'] = agent.load_prediction_agent( h5py.File(predict_agent, 'r')) if agent_type == 'q': q_bot = rl.load_q_agent(h5py.File(q_agent, 'r')) q_bot.set_temperature(0.01) bots['q'] = q_bot if agent_type == 'ac': ac_bot = rl.load_ac_agent(h5py.File(ac_agent, 'r')) ac_bot.set_temperature(0.05) bots['ac'] = ac_bot web_app = httpfrontend.get_web_app(bots) web_app.run(host=bind_address, port=port, threaded=False)
# tag::run_alphago[] from dlgo.agent import load_prediction_agent, load_policy_agent, AlphaGoMCTS from dlgo.rl import load_value_agent import h5py fast_policy = load_prediction_agent(h5py.File('alphago_sl_policy.h5', 'r')) strong_policy = load_policy_agent(h5py.File('alphago_rl_policy.h5', 'r')) value = load_value_agent(h5py.File('alphago_value.h5', 'r')) alphago = AlphaGoMCTS(strong_policy, fast_policy, value) # end::run_alphago[] # TODO: register in frontend
from dlgo.agent.naive import RandomBot from dlgo.agent import load_prediction_agent from dlgo.httpfrontend.server import get_web_app import h5py bots = {} random_agent = RandomBot() # bot_agent = load_prediction_agent(h5py.File("agents/GHGHbot1_rl_policy.h5", "r")) bot_agent = load_prediction_agent(h5py.File('agents/deep_bot_2.h5', "r")) web_app = get_web_app({'random': random_agent, 'predict': bot_agent}) web_app.run(threaded=False)
from dlgo.agent import load_prediction_agent, load_policy_agent, AlphaGoMCTS from dlgo.rl import load_value_agent import h5py fast_policy = load_prediction_agent(h5py.File('agents/GHGHbot1_sl_policy.h5', 'r')) strong_policy = load_policy_agent(h5py.File('agents/GHGHbot1_rl_policy.h5', 'r')) value = load_value_agent(h5py.File('agents/GHGHbot1_value.h5', 'r')) alphago = AlphaGoMCTS(strong_policy, fast_policy, value) # TODO: register in frontend