gomoku / DI-engine /dizoo /evogym /config /carrier_ppo_config.py
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init space
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from easydict import EasyDict
carry_ppo_config = dict(
exp_name='evogym_carrier_ppo_seed1',
env=dict(
env_id='Carrier-v0',
robot='carry_bot',
robot_dir='./dizoo/evogym/envs',
collector_env_num=8,
evaluator_env_num=8,
n_evaluator_episode=8,
stop_value=10,
manager=dict(shared_memory=True, ),
# The path to save the game replay
# replay_path='./evogym_carry_ppo_seed0/video',
),
policy=dict(
cuda=True,
recompute_adv=True,
# load_path="./evogym_carry_ppo_seed0/ckpt/ckpt_best.pth.tar",
model=dict(
obs_shape=70,
action_shape=12,
action_space='continuous',
),
action_space='continuous',
learn=dict(
epoch_per_collect=10,
batch_size=256,
learning_rate=3e-3,
value_weight=0.5,
entropy_weight=0.01,
clip_ratio=0.2,
adv_norm=True,
value_norm=True,
),
collect=dict(
n_sample=2048,
gae_lambda=0.97,
),
eval=dict(evaluator=dict(eval_freq=5000, )),
)
)
carry_ppo_config = EasyDict(carry_ppo_config)
main_config = carry_ppo_config
carry_ppo_create_config = dict(
env=dict(
type='evogym',
import_names=['dizoo.evogym.envs.evogym_env'],
),
env_manager=dict(type='subprocess'),
policy=dict(
type='ppo',
import_names=['ding.policy.ppo'],
),
replay_buffer=dict(type='naive', ),
)
carry_ppo_create_config = EasyDict(carry_ppo_create_config)
create_config = carry_ppo_create_config
if __name__ == "__main__":
# or you can enter `ding -m serial -c evogym_carry_ppo_config.py -s 0 --env-step 1e7`
from ding.entry import serial_pipeline_onpolicy
serial_pipeline_onpolicy((main_config, create_config), seed=0)