ding.config.example.TD3.gym_pendulum_v1

ding.config.example.TD3.gym_pendulum_v1

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../ding/config/example/TD3/gym_pendulum_v1.py

1from easydict import EasyDict 2import ding.envs.gym_env 3 4cfg = dict( 5 exp_name='Pendulum-v1-TD3', 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=True, 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=2, 32 noise=True, 33 noise_sigma=0.1, 34 noise_range=dict( 35 min=-0.5, 36 max=0.5, 37 ), 38 ), 39 collect=dict( 40 n_sample=48, 41 noise_sigma=0.1, 42 collector=dict(collect_print_freq=1000, ), 43 ), 44 eval=dict(evaluator=dict(eval_freq=100, ), ), 45 other=dict(replay_buffer=dict(replay_buffer_size=20000, ), ), 46 ), 47 wandb_logger=dict( 48 gradient_logger=True, video_logger=True, plot_logger=True, action_logger=True, return_logger=False 49 ), 50) 51 52cfg = EasyDict(cfg) 53 54env = ding.envs.gym_env.env