DI-engine/ding/config/example/DDPG/gym_pendulum_v1.py

from easydict import EasyDict
import ding.envs.gym_env

cfg = dict(
    exp_name='Pendulum-v1-DDPG',
    seed=0,
    env=dict(
        env_id='Pendulum-v1',
        collector_env_num=8,
        evaluator_env_num=5,
        n_evaluator_episode=5,
        stop_value=-250,
        act_scale=True,
    ),
    policy=dict(
        cuda=False,
        priority=False,
        random_collect_size=800,
        model=dict(
            obs_shape=3,
            action_shape=1,
            twin_critic=False,
            action_space='regression',
        ),
        learn=dict(
            update_per_collect=2,
            batch_size=128,
            learning_rate_actor=0.001,
            learning_rate_critic=0.001,
            ignore_done=True,
            actor_update_freq=1,
            noise=False,
        ),
        collect=dict(
            n_sample=48,
            noise_sigma=0.1,
            collector=dict(collect_print_freq=1000, ),
        ),
        eval=dict(evaluator=dict(eval_freq=100, )),
        other=dict(replay_buffer=dict(
            replay_buffer_size=20000,
            max_use=16,
        ), ),
    ),
    wandb_logger=dict(
        gradient_logger=True, video_logger=True, plot_logger=True, action_logger=True, return_logger=False
    ),
)

cfg = EasyDict(cfg)

env = ding.envs.gym_env.env