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from easydict import EasyDict
hopper_td3_bc_config = dict(
exp_name='hopper_td3_bc_seed0',
env=dict(
env_id='Hopper-v3',
norm_obs=dict(
use_norm=True,
offline_stats=dict(use_offline_stats=True, ),
),
norm_reward=dict(use_norm=False, ),
collector_env_num=1,
evaluator_env_num=8,
n_evaluator_episode=8,
stop_value=6000,
),
policy=dict(
cuda=True,
model=dict(
obs_shape=11,
action_shape=3,
twin_critic=True,
actor_head_hidden_size=256,
critic_head_hidden_size=256,
action_space='regression',
),
learn=dict(
train_epoch=30000,
batch_size=256,
learning_rate_actor=3e-4,
learning_rate_critic=3e-4,
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,
),
alpha=2.5,
),
collect=dict(
unroll_len=1,
noise_sigma=0.1,
data_type='hdf5',
# Users should add their own data path here. Data path should lead to a file to store data or load the stored data.
# Absolute path is recommended.
# In DI-engine, it is usually located in ``exp_name`` directory
data_path='data_path_placeholder',
),
command=dict(),
eval=dict(evaluator=dict(eval_freq=1000, )),
other=dict(replay_buffer=dict(replay_buffer_size=2000000, ), ),
),
)
hopper_td3_bc_config = EasyDict(hopper_td3_bc_config)
main_config = hopper_td3_bc_config
hopper_td3_bc_create_config = dict(
env=dict(
type='mujoco',
import_names=['dizoo.mujoco.envs.mujoco_env'],
),
env_manager=dict(type='subprocess'),
policy=dict(
type='td3_bc',
import_names=['ding.policy.td3_bc'],
),
replay_buffer=dict(type='naive', ),
)
hopper_td3_bc_create_config = EasyDict(hopper_td3_bc_create_config)
create_config = hopper_td3_bc_create_config
# if __name__ == "__main__":
# # or you can enter `ding -m serial -c hopper_td3_bc_config.py -s 0`
# from ding.entry import serial_pipeline
# serial_pipeline([main_config, create_config], seed=0)
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