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from easydict import EasyDict
hopper_bco_config = dict(
exp_name='hopper_bco_seed0',
env=dict(
env_id='Hopper-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,
),
policy=dict(
# Whether to use cuda for network.
cuda=True,
continuous=True,
loss_type='l1_loss',
model=dict(
obs_shape=11,
action_shape=3,
action_space='regression',
actor_head_hidden_size=128,
),
learn=dict(
train_epoch=20,
batch_size=128,
learning_rate=0.001,
weight_decay=1e-4,
momentum=0.9,
decay_epoch=30,
decay_rate=1,
warmup_lr=1e-4,
warmup_epoch=3,
optimizer='SGD',
lr_decay=True,
),
collect=dict(
n_episode=100,
# control the number (alpha*n_episode) of post-demonstration environment interactions at each iteration.
# Notice: alpha * n_episode > collector_env_num
model_path='abs model path', # expert model path
data_path='abs data path', # expert data path
noise=True,
noise_sigma=dict(
start=0.5,
end=0.1,
decay=1000000,
type='exp',
),
noise_range=dict(
min=-1,
max=1,
),
),
eval=dict(evaluator=dict(eval_freq=40, )),
other=dict(replay_buffer=dict(replay_buffer_size=100000, ), ),
),
bco=dict(
learn=dict(idm_batch_size=256, idm_learning_rate=0.001, idm_weight_decay=0, idm_train_epoch=20),
model=dict(
action_space='regression',
idm_encoder_hidden_size_list=[60, 80, 100, 40],
),
alpha=0.2,
)
)
hopper_bco_config = EasyDict(hopper_bco_config)
main_config = hopper_bco_config
hopper_bco_create_config = dict(
env=dict(
type='mujoco',
import_names=['dizoo.mujoco.envs.mujoco_env'],
),
env_manager=dict(type='subprocess'),
policy=dict(type='bc'),
collector=dict(type='episode'),
)
hopper_bco_create_config = EasyDict(hopper_bco_create_config)
create_config = hopper_bco_create_config
if __name__ == "__main__":
from ding.entry import serial_pipeline_bco
from dizoo.mujoco.config.hopper_sac_config import hopper_sac_config, hopper_sac_create_config
expert_main_config = hopper_sac_config
expert_create_config = hopper_sac_create_config
serial_pipeline_bco(
[main_config, create_config], [expert_main_config, expert_create_config], seed=0, max_env_step=3000000
)
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