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from easydict import EasyDict | |
import ding.envs.gym_env | |
cfg = dict( | |
exp_name='LunarLander-v2-DQN', | |
seed=0, | |
env=dict( | |
env_id='LunarLander-v2', | |
collector_env_num=8, | |
evaluator_env_num=8, | |
n_evaluator_episode=8, | |
stop_value=260, | |
), | |
policy=dict( | |
cuda=True, | |
random_collect_size=25000, | |
discount_factor=0.99, | |
nstep=3, | |
learn=dict( | |
update_per_collect=10, | |
batch_size=64, | |
learning_rate=0.001, | |
# Frequency of target network update. | |
target_update_freq=100, | |
), | |
model=dict( | |
obs_shape=8, | |
action_shape=4, | |
encoder_hidden_size_list=[512, 64], | |
# Whether to use dueling head. | |
dueling=True, | |
), | |
collect=dict( | |
n_sample=64, | |
unroll_len=1, | |
), | |
other=dict( | |
eps=dict( | |
type='exp', | |
start=0.95, | |
end=0.1, | |
decay=50000, | |
), replay_buffer=dict(replay_buffer_size=100000, ) | |
), | |
), | |
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 | |