Spaces:
Sleeping
Sleeping
| from easydict import EasyDict | |
| lunarlander_sac_config = dict( | |
| exp_name='lunarlander_cont_sac_seed0', | |
| env=dict( | |
| env_id='LunarLanderContinuous-v2', | |
| collector_env_num=4, | |
| evaluator_env_num=8, | |
| # (bool) Scale output action into legal range. | |
| act_scale=True, | |
| n_evaluator_episode=8, | |
| stop_value=200, | |
| ), | |
| policy=dict( | |
| cuda=False, | |
| random_collect_size=10000, | |
| model=dict( | |
| obs_shape=8, | |
| action_shape=2, | |
| twin_critic=True, | |
| action_space='reparameterization', | |
| ), | |
| learn=dict( | |
| update_per_collect=256, | |
| batch_size=128, | |
| learning_rate_q=1e-3, | |
| learning_rate_policy=3e-4, | |
| learning_rate_alpha=3e-4, | |
| auto_alpha=True, | |
| ), | |
| collect=dict(n_sample=256, ), | |
| eval=dict(evaluator=dict(eval_freq=1000, ), ), | |
| other=dict(replay_buffer=dict(replay_buffer_size=int(1e5), ), ), | |
| ), | |
| ) | |
| lunarlander_sac_config = EasyDict(lunarlander_sac_config) | |
| main_config = lunarlander_sac_config | |
| lunarlander_sac_create_config = dict( | |
| env=dict( | |
| type='lunarlander', | |
| import_names=['dizoo.box2d.lunarlander.envs.lunarlander_env'], | |
| ), | |
| env_manager=dict(type='subprocess'), | |
| policy=dict(type='sac'), | |
| ) | |
| lunarlander_sac_create_config = EasyDict(lunarlander_sac_create_config) | |
| create_config = lunarlander_sac_create_config | |
| if __name__ == '__main__': | |
| # or you can enter `ding -m serial -c lunarlander_cont_sac_config.py -s 0` | |
| from ding.entry import serial_pipeline | |
| serial_pipeline([main_config, create_config], seed=0) | |