RL_Book/main.py at main · nxtlevYeah/RL_Book · GitHub

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# This file is part of RL_Book Project.
#
# Copyright (C) 2025 SeongJin Yoon
#
# RL_Book is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# RL_Book is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <https://www.gnu.org/licenses/>.
"""main.py: 강화학습 프레임워크 실행 프로그램."""
import torch
import numpy as np
import random
import utils.config as cu
import argparse
from runner.runner import Runner
from runner.multienv_runner import MultiEnvRunner
from runner.multienv_async_runner import MultiEnvAsyncRunner

if __name__ == '__main__':

    # 1. 명령어 인자 파서 생성
    desc = 'RL Framework'
    parser = argparse.ArgumentParser(description=desc)

    # 2. 에이전트 이름 인자 추가
    parser.add_argument('-a',
                        '--agent',
                        help='agent name {'
                             'reinforce, '
                             'reinforce_b, '
                             'a2c, '
                             'dqn, '
                             'ddqn, '
                             'ppo, '
                             '}',
                        type=str,
                        default='reinforce')

    # 3. 환경 이름 인자 추가
    parser.add_argument('-e',
                        '--env',
                        help='run type {'
                             'CartPole-v1, '
                             'LunarLanderContinuous-v3, '
                             'Acrobot-v1, '
                             'AntBulletEnv-v0,'
                             'BFenv'
                             '}',
                        type=str,
                        default='CartPole-v1')

    # 4. 명령어 인자 파싱
    args = parser.parse_args()

    # 5. 난수 발생기 씨드 랜덤 생성
    random_seed = random.randrange(0, 16546)

    # 6. 난수 발생기를 초기화
    np.random.seed(random_seed)
    torch.manual_seed(random_seed)

    print("!"*30)
    print("random_seed=", random_seed)
    print("!"*30)

    # 7. 에이전트 이름과 환경 이름 받기
    agent_name = args.agent
    env_name = args.env

    # 8. 설정 파일 읽기
    config: dict = cu.config_copy(cu.get_config(agent_name, env_name))

    # 9. 설정 값 추가
    config['agent'] = agent_name                # 에이전트 이름 추가
    config['env_name'] = env_name               # 환경 이름 추가
    config['random_seed'] = random_seed         # 난수발생기 씨드 추가
    if config.get('env_args', None) is None:    # 환경 인자 기본값 처리
        config['env_args'] = {}

    # 10. 러너 클래스 선택
    config['distributed_processing_type'] = \
        config.get('distributed_processing_type',"sync")
    if config['n_envs'] == 1:
        RunnerClass = Runner
    elif config['distributed_processing_type'] == "sync":
        RunnerClass = MultiEnvRunner
    else:
        RunnerClass = MultiEnvAsyncRunner

    # 11. 러너의 run() 메서드 호출
    RunnerClass(config).run()