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from easydict import EasyDict
walker_ppo_config = dict(
exp_name='evogym_walker_ppo_seed0',
env=dict(
env_id='Walker-v0',
robot='speed_bot',
robot_dir='./dizoo/evogym/envs',
collector_env_num=1,
evaluator_env_num=1,
n_evaluator_episode=1,
stop_value=10,
manager=dict(shared_memory=True, ),
# The path to save the game replay
# replay_path='./evogym_walker_ppo_seed0/video',
),
policy=dict(
cuda=True,
recompute_adv=True,
# load_path="./evogym_walker_ppo_seed0/ckpt/ckpt_best.pth.tar",
model=dict(
obs_shape=58,
action_shape=10,
action_space='continuous',
),
action_space='continuous',
learn=dict(
epoch_per_collect=10,
batch_size=256,
learning_rate=3e-4,
value_weight=0.5,
entropy_weight=0.0,
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, )),
)
)
walker_ppo_config = EasyDict(walker_ppo_config)
main_config = walker_ppo_config
walker_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', ),
)
walker_ppo_create_config = EasyDict(walker_ppo_create_config)
create_config = walker_ppo_create_config
if __name__ == "__main__":
# or you can enter `ding -m serial -c evogym_walker_ppo_config.py -s 0 --env-step 1e7`
from ding.entry import serial_pipeline_onpolicy
serial_pipeline_onpolicy((main_config, create_config), seed=0)
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