ding.config.example.DDPG.gym_pendulum_v1

ding.config.example.DDPG.gym_pendulum_v1

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../ding/config/example/DDPG/gym_pendulum_v1.py

1from easydict import EasyDict 2import ding.envs.gym_env 3 4cfg = dict( 5 exp_name='Pendulum-v1-DDPG', 6 seed=0, 7 env=dict( 8 env_id='Pendulum-v1', 9 collector_env_num=8, 10 evaluator_env_num=5, 11 n_evaluator_episode=5, 12 stop_value=-250, 13 act_scale=True, 14 ), 15 policy=dict( 16 cuda=False, 17 priority=False, 18 random_collect_size=800, 19 model=dict( 20 obs_shape=3, 21 action_shape=1, 22 twin_critic=False, 23 action_space='regression', 24 ), 25 learn=dict( 26 update_per_collect=2, 27 batch_size=128, 28 learning_rate_actor=0.001, 29 learning_rate_critic=0.001, 30 ignore_done=True, 31 actor_update_freq=1, 32 noise=False, 33 ), 34 collect=dict( 35 n_sample=48, 36 noise_sigma=0.1, 37 collector=dict(collect_print_freq=1000, ), 38 ), 39 eval=dict(evaluator=dict(eval_freq=100, )), 40 other=dict(replay_buffer=dict( 41 replay_buffer_size=20000, 42 max_use=16, 43 ), ), 44 ), 45 wandb_logger=dict( 46 gradient_logger=True, video_logger=True, plot_logger=True, action_logger=True, return_logger=False 47 ), 48) 49 50cfg = EasyDict(cfg) 51 52env = ding.envs.gym_env.env