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from easydict import EasyDict
import ding.envs.gym_env
cfg = dict(
exp_name='Pendulum-v1-SAC',
seed=0,
env=dict(
env_id='Pendulum-v1',
collector_env_num=10,
evaluator_env_num=8,
n_evaluator_episode=8,
stop_value=-250,
act_scale=True,
),
policy=dict(
cuda=True,
priority=False,
random_collect_size=1000,
model=dict(
obs_shape=3,
action_shape=1,
twin_critic=True,
action_space='reparameterization',
actor_head_hidden_size=128,
critic_head_hidden_size=128,
),
learn=dict(
update_per_collect=1,
batch_size=128,
learning_rate_q=0.001,
learning_rate_policy=0.001,
learning_rate_alpha=0.0003,
ignore_done=True,
target_theta=0.005,
discount_factor=0.99,
auto_alpha=True,
),
collect=dict(n_sample=10, ),
eval=dict(evaluator=dict(eval_freq=100, )),
other=dict(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
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