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| from easydict import EasyDict | |
| agent_num = 3 | |
| obs_dim = 26 | |
| collector_env_num = 8 | |
| evaluator_env_num = 32 | |
| main_config = dict( | |
| exp_name='gfootball_keeper_mappo_seed0', | |
| env=dict( | |
| env_name='academy_3_vs_1_with_keeper', | |
| agent_num=agent_num, | |
| obs_dim=obs_dim, | |
| n_evaluator_episode=32, | |
| stop_value=1, | |
| collector_env_num=collector_env_num, | |
| evaluator_env_num=evaluator_env_num, | |
| manager=dict( | |
| shared_memory=False, | |
| reset_timeout=6000, | |
| ), | |
| ), | |
| policy=dict( | |
| cuda=True, | |
| multi_agent=True, | |
| model=dict( | |
| # (int) obs_shape: The shapeof observation of each agent. | |
| # (int) global_obs_shape: The shape of global observation. | |
| agent_obs_shape=obs_dim, | |
| global_obs_shape=int(obs_dim * 2), | |
| # (int) action_shape: The number of action which each agent can take. | |
| action_shape=19, | |
| ), | |
| learn=dict( | |
| epoch_per_collect=10, | |
| batch_size=3200, | |
| learning_rate=5e-4, | |
| # ============================================================== | |
| # The following configs is algorithm-specific | |
| # ============================================================== | |
| # (float) The loss weight of value network, policy network weight is set to 1 | |
| value_weight=0.5, | |
| # (float) The loss weight of entropy regularization, policy network weight is set to 1 | |
| entropy_weight=0.01, | |
| # (float) PPO clip ratio, defaults to 0.2 | |
| clip_ratio=0.05, | |
| # (bool) Whether to use advantage norm in a whole training batch | |
| adv_norm=False, | |
| value_norm=True, | |
| ppo_param_init=True, | |
| grad_clip_type='clip_norm', | |
| grad_clip_value=10, | |
| ignore_done=False, | |
| ), | |
| collect=dict(env_num=collector_env_num, n_sample=3200), | |
| eval=dict(env_num=evaluator_env_num, evaluator=dict(eval_freq=50, )), | |
| ), | |
| ) | |
| main_config = EasyDict(main_config) | |
| create_config = dict( | |
| env=dict( | |
| type='gfootball-academy', | |
| import_names=['dizoo.gfootball.envs.gfootball_academy_env'], | |
| ), | |
| env_manager=dict(type='subprocess'), | |
| policy=dict(type='ppo'), | |
| ) | |
| create_config = EasyDict(create_config) | |
| if __name__ == "__main__": | |
| # or you can enter `ding -m serial_onpolicy -c gfootball_keeper_mappo_config.py -s 0` | |
| from ding.entry import serial_pipeline_onpolicy | |
| serial_pipeline_onpolicy([main_config, create_config], seed=0) | |