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| from easydict import EasyDict | |
| collector_env_num = 8 | |
| evaluator_env_num = 5 | |
| gfootball_dqn_main_config = dict( | |
| exp_name='gfootball_dqn_seed0', | |
| env=dict( | |
| collector_env_num=collector_env_num, | |
| evaluator_env_num=evaluator_env_num, | |
| n_evaluator_episode=evaluator_env_num, | |
| stop_value=999, | |
| env_name="11_vs_11_easy_stochastic", | |
| # env_name="11_vs_11_stochastic", # default: medium | |
| # env_name="11_vs_11_hard_stochastic", | |
| save_replay_gif=False, | |
| manager=dict(shared_memory=False, ), | |
| ), | |
| policy=dict( | |
| cuda=True, | |
| nstep=5, | |
| discount_factor=0.997, | |
| model=dict(), | |
| learn=dict( | |
| update_per_collect=20, | |
| batch_size=512, | |
| learning_rate=0.0001, | |
| target_update_freq=500, | |
| ), | |
| collect=dict(n_sample=256), | |
| eval=dict(evaluator=dict(eval_freq=5000)), | |
| other=dict( | |
| eps=dict( | |
| type='exp', | |
| start=1, | |
| end=0.05, | |
| decay=int(2e5), | |
| ), | |
| replay_buffer=dict(replay_buffer_size=int(5e5), ), | |
| ), | |
| ), | |
| ) | |
| gfootball_dqn_main_config = EasyDict(gfootball_dqn_main_config) | |
| main_config = gfootball_dqn_main_config | |
| gfootball_dqn_create_config = dict( | |
| env=dict( | |
| type='gfootball', | |
| import_names=['dizoo.gfootball.envs.gfootball_env'], | |
| ), | |
| env_manager=dict(type='subprocess'), | |
| policy=dict(type='dqn'), | |
| ) | |
| gfootball_dqn_create_config = EasyDict(gfootball_dqn_create_config) | |
| create_config = gfootball_dqn_create_config | |
| if __name__ == '__main__': | |
| from ding.entry import serial_pipeline | |
| from dizoo.gfootball.model.q_network.football_q_network import FootballNaiveQ | |
| football_naive_q = FootballNaiveQ() | |
| serial_pipeline((main_config, create_config), model=football_naive_q, seed=0, max_env_step=int(5e6)) | |