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from easydict import EasyDict | |
import ding.envs.gym_env | |
cfg = dict( | |
exp_name='LunarLander-v2-SQL', | |
env=dict( | |
collector_env_num=8, | |
evaluator_env_num=8, | |
env_id='LunarLander-v2', | |
n_evaluator_episode=8, | |
stop_value=260, | |
), | |
policy=dict( | |
cuda=True, | |
model=dict( | |
obs_shape=8, | |
action_shape=4, | |
encoder_hidden_size_list=[128, 128, 64], | |
dueling=True, | |
), | |
nstep=1, | |
discount_factor=0.97, | |
learn=dict(batch_size=64, learning_rate=0.001, alpha=0.08), | |
collect=dict(n_sample=64), | |
eval=dict(evaluator=dict(eval_freq=50, )), # note: this is the times after which you learns to evaluate | |
other=dict( | |
eps=dict( | |
type='exp', | |
start=0.95, | |
end=0.1, | |
decay=10000, | |
), | |
replay_buffer=dict(replay_buffer_size=20000, ), | |
), | |
), | |
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 | |