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)