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| # You can conduct Experiments on D4RL with this config file through the following command: | |
| # cd ../entry && python d4rl_td3_bc_main.py | |
| from easydict import EasyDict | |
| main_config = dict( | |
| exp_name='hopper_medium_td3-bc_seed0', | |
| env=dict( | |
| env_id='hopper-medium-v2', | |
| collector_env_num=1, | |
| evaluator_env_num=8, | |
| use_act_scale=True, | |
| n_evaluator_episode=8, | |
| stop_value=6000, | |
| ), | |
| policy=dict( | |
| cuda=True, | |
| model=dict( | |
| obs_shape=11, | |
| action_shape=3, | |
| ), | |
| learn=dict( | |
| train_epoch=30000, | |
| batch_size=256, | |
| learning_rate_actor=0.0003, | |
| learning_rate_critic=0.0003, | |
| actor_update_freq=2, | |
| noise=True, | |
| noise_sigma=0.2, | |
| noise_range={ | |
| 'min': -0.5, | |
| 'max': 0.5 | |
| }, | |
| alpha=2.5, | |
| ), | |
| collect=dict( | |
| data_type='d4rl', | |
| data_path=None, | |
| ), | |
| eval=dict(evaluator=dict(eval_freq=10000, )), | |
| other=dict(replay_buffer=dict(replay_buffer_size=2000000, ), ), | |
| ), | |
| ) | |
| main_config = EasyDict(main_config) | |
| main_config = main_config | |
| create_config = dict( | |
| env=dict( | |
| type='d4rl', | |
| import_names=['dizoo.d4rl.envs.d4rl_env'], | |
| ), | |
| env_manager=dict( | |
| cfg_type='BaseEnvManagerDict', | |
| type='base', | |
| ), | |
| policy=dict( | |
| type='td3_bc', | |
| import_names=['ding.policy.td3_bc'], | |
| ), | |
| replay_buffer=dict(type='naive', ), | |
| ) | |
| create_config = EasyDict(create_config) | |
| create_config = create_config | |