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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
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