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from easydict import EasyDict
import ding.envs.gym_env
cfg = dict(
exp_name='Walker2d-v3-TD3',
seed=0,
env=dict(
env_id='Walker2d-v3',
norm_obs=dict(use_norm=False, ),
norm_reward=dict(use_norm=False, ),
collector_env_num=1,
evaluator_env_num=8,
n_evaluator_episode=8,
stop_value=6000,
env_wrapper='mujoco_default',
),
policy=dict(
cuda=True,
random_collect_size=25000,
model=dict(
obs_shape=17,
action_shape=6,
twin_critic=True,
actor_head_hidden_size=256,
critic_head_hidden_size=256,
action_space='regression',
),
learn=dict(
update_per_collect=1,
batch_size=256,
learning_rate_actor=1e-3,
learning_rate_critic=1e-3,
ignore_done=False,
target_theta=0.005,
discount_factor=0.99,
actor_update_freq=2,
noise=True,
noise_sigma=0.2,
noise_range=dict(
min=-0.5,
max=0.5,
),
),
collect=dict(
n_sample=1,
unroll_len=1,
noise_sigma=0.1,
),
other=dict(replay_buffer=dict(replay_buffer_size=1000000, ), ),
),
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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