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from easydict import EasyDict
maze_ppg_config = dict(
exp_name='maze_ppg_seed0',
env=dict(
is_train=True,
env_id='maze',
collector_env_num=64,
evaluator_env_num=10,
n_evaluator_episode=50,
stop_value=10,
manager=dict(shared_memory=True, ),
),
policy=dict(
cuda=True,
model=dict(
obs_shape=[3, 64, 64],
action_shape=15,
encoder_hidden_size_list=[16, 32, 32],
actor_head_hidden_size=256,
critic_head_hidden_size=256,
impala_cnn_encoder=True,
),
learn=dict(
learning_rate=0.0005,
actor_epoch_per_collect=1,
critic_epoch_per_collect=1,
value_norm=False,
batch_size=2048,
value_weight=1.0,
entropy_weight=0.01,
clip_ratio=0.2,
aux_freq=1,
),
collect=dict(
n_sample=16384,
discount_factor=0.99,
),
eval=dict(evaluator=dict(eval_freq=24, )),
other=dict(),
),
)
maze_ppg_config = EasyDict(maze_ppg_config)
main_config = maze_ppg_config
maze_ppg_create_config = dict(
env=dict(
type='procgen',
import_names=['dizoo.procgen.envs.procgen_env'],
),
env_manager=dict(type='subprocess', ),
policy=dict(type='ppg'),
)
maze_ppg_create_config = EasyDict(maze_ppg_create_config)
create_config = maze_ppg_create_config
if __name__ == "__main__":
from ding.entry import serial_pipeline_onpolicy_ppg
serial_pipeline_onpolicy_ppg([main_config, create_config], seed=0)
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