from easydict import EasyDict hopper_td3_bc_config = dict( exp_name='hopper_td3_bc_seed0', env=dict( env_id='Hopper-v3', norm_obs=dict( use_norm=True, offline_stats=dict(use_offline_stats=True, ), ), norm_reward=dict(use_norm=False, ), collector_env_num=1, evaluator_env_num=8, n_evaluator_episode=8, stop_value=6000, ), policy=dict( cuda=True, model=dict( obs_shape=11, action_shape=3, twin_critic=True, actor_head_hidden_size=256, critic_head_hidden_size=256, action_space='regression', ), learn=dict( train_epoch=30000, batch_size=256, learning_rate_actor=3e-4, learning_rate_critic=3e-4, ignore_done=False, target_theta=0.005, discount_factor=0.99, actor_update_freq=2, noise=True, noise_sigma=0.2, noise_range=dict( min=-0.5, max=0.5, ), alpha=2.5, ), collect=dict( unroll_len=1, noise_sigma=0.1, data_type='hdf5', # 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', ), command=dict(), eval=dict(evaluator=dict(eval_freq=1000, )), other=dict(replay_buffer=dict(replay_buffer_size=2000000, ), ), ), ) hopper_td3_bc_config = EasyDict(hopper_td3_bc_config) main_config = hopper_td3_bc_config hopper_td3_bc_create_config = dict( env=dict( type='mujoco', import_names=['dizoo.mujoco.envs.mujoco_env'], ), env_manager=dict(type='subprocess'), policy=dict( type='td3_bc', import_names=['ding.policy.td3_bc'], ), replay_buffer=dict(type='naive', ), ) hopper_td3_bc_create_config = EasyDict(hopper_td3_bc_create_config) create_config = hopper_td3_bc_create_config # if __name__ == "__main__": # # or you can enter `ding -m serial -c hopper_td3_bc_config.py -s 0` # from ding.entry import serial_pipeline # serial_pipeline([main_config, create_config], seed=0)