from easydict import EasyDict qbert_onppo_config = dict( exp_name='enduro_onppo_seed0', env=dict( collector_env_num=16, evaluator_env_num=8, n_evaluator_episode=8, stop_value=int(1e10), env_id='QbertNoFrameskip-v4', #'ALE/Qbert-v5' is available. But special setting is needed after gym make. frame_stack=4 ), policy=dict( cuda=True, recompute_adv=True, action_space='discrete', model=dict( obs_shape=[4, 84, 84], action_shape=6, action_space='discrete', encoder_hidden_size_list=[64, 64, 128], actor_head_hidden_size=128, critic_head_hidden_size=128, ), learn=dict( epoch_per_collect=10, update_per_collect=1, batch_size=320, learning_rate=3e-4, value_weight=0.5, entropy_weight=0.001, clip_ratio=0.2, adv_norm=True, value_norm=True, # for onppo, when we recompute adv, we need the key done in data to split traj, so we must # use ignore_done=False here, # but when we add key traj_flag in data as the backup for key done, we could choose to use ignore_done=True # for halfcheetah, the length=1000 ignore_done=False, grad_clip_type='clip_norm', grad_clip_value=0.5, ), collect=dict( n_sample=3200, unroll_len=1, discount_factor=0.99, gae_lambda=0.95, ), eval=dict(evaluator=dict(eval_freq=5000, )), ), ) main_config = EasyDict(qbert_onppo_config) qbert_onppo_create_config = dict( env=dict( type='atari', import_names=['dizoo.atari.envs.atari_env'], ), env_manager=dict(type='subprocess'), policy=dict(type='ppo'), ) create_config = EasyDict(qbert_onppo_create_config) if __name__ == "__main__": # or you can enter ding -m serial_onpolicy -c qbert_onppo_config.py -s 0 from ding.entry import serial_pipeline_onpolicy serial_pipeline_onpolicy([main_config, create_config], seed=0)