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| from easydict import EasyDict | |
| bipedalwalker_bco_config = dict( | |
| exp_name='bipedalwalker_bco_seed0', | |
| env=dict( | |
| env_id='BipedalWalker-v3', | |
| collector_env_num=8, | |
| evaluator_env_num=5, | |
| # (bool) Scale output action into legal range. | |
| act_scale=True, | |
| n_evaluator_episode=5, | |
| stop_value=300, | |
| rew_clip=True, | |
| # The path to save the game replay | |
| replay_path=None, | |
| ), | |
| policy=dict( | |
| # Whether to use cuda for network. | |
| cuda=True, | |
| continuous=True, | |
| loss_type='l1_loss', | |
| model=dict( | |
| obs_shape=24, | |
| action_shape=4, | |
| action_space='regression', | |
| actor_head_hidden_size=128, | |
| ), | |
| learn=dict( | |
| train_epoch=30, | |
| batch_size=128, | |
| learning_rate=0.01, | |
| weight_decay=1e-4, | |
| decay_epoch=1000, | |
| decay_rate=0.5, | |
| warmup_lr=1e-4, | |
| warmup_epoch=3, | |
| optimizer='SGD', | |
| lr_decay=True, | |
| momentum=0.9, | |
| ), | |
| collect=dict( | |
| n_episode=100, | |
| # control the number (alpha*n_episode) of post-demonstration environment interactions at each iteration. | |
| # Notice: alpha * n_episode > collector_env_num | |
| model_path='abs model path', # expert model path | |
| data_path='abs data path', # expert data path | |
| noise=True, | |
| noise_sigma=dict( | |
| start=0.5, | |
| end=0.1, | |
| decay=1000000, | |
| type='exp', | |
| ), | |
| noise_range=dict( | |
| min=-1, | |
| max=1, | |
| ), | |
| ), | |
| eval=dict(evaluator=dict(eval_freq=100, )), | |
| other=dict(replay_buffer=dict(replay_buffer_size=100000, ), ), | |
| ), | |
| bco=dict( | |
| learn=dict(idm_batch_size=128, idm_learning_rate=0.001, idm_weight_decay=0, idm_train_epoch=50), | |
| model=dict( | |
| action_space='regression', | |
| idm_encoder_hidden_size_list=[60, 80, 100, 40], | |
| ), | |
| alpha=0.2, | |
| ) | |
| ) | |
| bipedalwalker_bco_config = EasyDict(bipedalwalker_bco_config) | |
| main_config = bipedalwalker_bco_config | |
| bipedalwalker_bco_create_config = dict( | |
| env=dict( | |
| type='bipedalwalker', | |
| import_names=['dizoo.box2d.bipedalwalker.envs.bipedalwalker_env'], | |
| ), | |
| env_manager=dict(type='base'), | |
| policy=dict(type='bc'), | |
| collector=dict(type='episode'), | |
| ) | |
| bipedalwalker_bco_create_config = EasyDict(bipedalwalker_bco_create_config) | |
| create_config = bipedalwalker_bco_create_config | |
| if __name__ == "__main__": | |
| from ding.entry import serial_pipeline_bco | |
| from dizoo.box2d.bipedalwalker.config import bipedalwalker_sac_config, bipedalwalker_sac_create_config | |
| expert_main_config = bipedalwalker_sac_config | |
| expert_create_config = bipedalwalker_sac_create_config | |
| serial_pipeline_bco( | |
| [main_config, create_config], [expert_main_config, expert_create_config], seed=0, max_env_step=2000000 | |
| ) | |