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from easydict import EasyDict
halfcheetah_td3_config = dict(
exp_name='halfcheetah_td3_seed0',
env=dict(
env_id='HalfCheetah-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=11000,
),
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=True,
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, ), ),
)
)
halfcheetah_td3_config = EasyDict(halfcheetah_td3_config)
main_config = halfcheetah_td3_config
halfcheetah_td3_create_config = dict(
env=dict(
type='mujoco',
import_names=['dizoo.mujoco.envs.mujoco_env'],
),
env_manager=dict(type='subprocess'),
policy=dict(
type='td3',
import_names=['ding.policy.td3'],
),
replay_buffer=dict(type='naive', ),
)
halfcheetah_td3_create_config = EasyDict(halfcheetah_td3_create_config)
create_config = halfcheetah_td3_create_config
if __name__ == "__main__":
# or you can enter `ding -m serial -c halfcheetah_td3_config.py -s 0 --env-step 1e7`
from ding.entry import serial_pipeline
serial_pipeline((main_config, create_config), seed=0)
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