from easydict import EasyDict qbert_cql_config = dict( exp_name='qbert_cql_seed0', env=dict( collector_env_num=8, evaluator_env_num=8, n_evaluator_episode=8, stop_value=30000, env_id='QbertNoFrameskip-v4', #'ALE/Qbert-v5' is available. But special setting is needed after gym make. frame_stack=4 ), policy=dict( cuda=True, priority=False, model=dict( obs_shape=[4, 84, 84], action_shape=6, encoder_hidden_size_list=[128, 128, 512], num_quantiles=200, ), nstep=1, discount_factor=0.99, learn=dict( update_per_collect=10, train_epoch=30000, batch_size=32, learning_rate=0.0001, target_update_freq=2000, min_q_weight=10.0, ), collect=dict( n_sample=100, data_type='naive', # Users should add their own data path here. Data path should lead to a file to store data or load the stored data. # Absolute path is recommended. # In DI-engine, it is usually located in ``exp_name`` directory data_path='data_path_placeholder', ), eval=dict(evaluator=dict(eval_freq=4000, )), other=dict( eps=dict( type='exp', start=1., end=0.05, decay=1000000, ), replay_buffer=dict(replay_buffer_size=400000, ), ), ), ) main_config = EasyDict(qbert_cql_config) qbert_cql_create_config = dict( env=dict( type='atari', import_names=['dizoo.atari.envs.atari_env'], ), env_manager=dict(type='subprocess'), policy=dict(type='cql_discrete'), ) create_config = EasyDict(qbert_cql_create_config) if __name__ == '__main__': # or you can enter ding -m serial_offline -c qbert_cql_config.py -s 0 from ding.entry import serial_pipeline_offline serial_pipeline_offline((main_config, create_config), seed=0)