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from easydict import EasyDict
from ding.entry import serial_pipeline_onpolicy
slime_volley_ppo_config = dict(
exp_name='slime_volley_ppo_seed0',
env=dict(
collector_env_num=8,
evaluator_env_num=5,
n_evaluator_episode=5,
agent_vs_agent=False, # vs bot
stop_value=5, # 5 times per episode
env_id="SlimeVolley-v0",
),
policy=dict(
cuda=True,
action_space='discrete',
model=dict(
obs_shape=12,
action_shape=6,
action_space='discrete',
encoder_hidden_size_list=[64, 64],
critic_head_hidden_size=64,
actor_head_hidden_size=64,
share_encoder=False, # It is not wise to share encoder in low-dimension observation.
),
learn=dict(
epoch_per_collect=5,
batch_size=64,
learning_rate=3e-4,
entropy_weight=0.0, # [0.01, 0.0]
),
collect=dict(
n_sample=4096,
discount_factor=0.99,
gae_lambda=0.95,
),
),
)
slime_volley_ppo_config = EasyDict(slime_volley_ppo_config)
main_config = slime_volley_ppo_config
slime_volley_ppo_create_config = dict(
env=dict(
type='slime_volley',
import_names=['dizoo.slime_volley.envs.slime_volley_env'],
),
env_manager=dict(type='subprocess'), # if you want to save replay, it must use base
policy=dict(type='ppo'),
)
slime_volley_ppo_create_config = EasyDict(slime_volley_ppo_create_config)
create_config = slime_volley_ppo_create_config
if __name__ == "__main__":
serial_pipeline_onpolicy([main_config, create_config], seed=0)
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