from easydict import EasyDict hopper_cql_config = dict( exp_name='hopper_cql_seed0', env=dict( env_id='Hopper-v3', norm_obs=dict(use_norm=False, ), 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, action_space='reparameterization', actor_head_hidden_size=256, critic_head_hidden_size=256, ), learn=dict( train_epoch=30000, batch_size=256, learning_rate_q=3e-4, learning_rate_policy=1e-4, learning_rate_alpha=1e-4, ignore_done=False, target_theta=0.005, discount_factor=0.99, alpha=0.2, auto_alpha=False, with_lagrange=False, lagrange_thresh=-1.0, min_q_weight=5.0, ), collect=dict( unroll_len=1, 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', ), command=dict(), eval=dict(evaluator=dict(eval_freq=500, )), other=dict(replay_buffer=dict(replay_buffer_size=2000000, ), ), ), ) hopper_cql_config = EasyDict(hopper_cql_config) main_config = hopper_cql_config hopper_cql_create_config = dict( env=dict( type='mujoco', import_names=['dizoo.mujoco.envs.mujoco_env'], ), env_manager=dict(type='subprocess'), policy=dict( type='cql', import_names=['ding.policy.cql'], ), replay_buffer=dict(type='naive', ), ) hopper_cql_create_config = EasyDict(hopper_cql_create_config) create_config = hopper_cql_create_config