| from easydict import EasyDict | |
| import ding.envs.gym_env | |
| cfg = dict( | |
| exp_name='Bipedalwalker-v3-DDPG', | |
| seed=0, | |
| env=dict( | |
| env_id='BipedalWalker-v3', | |
| collector_env_num=8, | |
| evaluator_env_num=5, | |
| n_evaluator_episode=5, | |
| act_scale=True, | |
| rew_clip=True, | |
| ), | |
| policy=dict( | |
| cuda=True, | |
| random_collect_size=10000, | |
| model=dict( | |
| obs_shape=24, | |
| action_shape=4, | |
| twin_critic=False, | |
| action_space='regression', | |
| actor_head_hidden_size=400, | |
| critic_head_hidden_size=400, | |
| ), | |
| learn=dict( | |
| update_per_collect=64, | |
| batch_size=256, | |
| learning_rate_actor=0.0003, | |
| learning_rate_critic=0.0003, | |
| target_theta=0.005, | |
| discount_factor=0.99, | |
| learner=dict(hook=dict(log_show_after_iter=1000, )) | |
| ), | |
| collect=dict(n_sample=64, ), | |
| other=dict(replay_buffer=dict(replay_buffer_size=300000, ), ), | |
| ), | |
| 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 | |