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| from easydict import EasyDict | |
| pendulum_cql_config = dict( | |
| exp_name='pendulum_cql', | |
| env=dict( | |
| evaluator_env_num=5, | |
| act_scale=True, | |
| n_evaluator_episode=5, | |
| stop_value=-250, | |
| ), | |
| policy=dict( | |
| cuda=True, | |
| model=dict( | |
| obs_shape=3, | |
| action_shape=1, | |
| twin_critic=True, | |
| action_space='reparameterization', | |
| actor_head_hidden_size=128, | |
| critic_head_hidden_size=128, | |
| ), | |
| learn=dict( | |
| train_epoch=30000, | |
| batch_size=128, | |
| learning_rate_q=3e-4, | |
| learning_rate_policy=1e-3, | |
| learning_rate_alpha=1e-3, | |
| ignore_done=True, | |
| target_theta=0.005, | |
| discount_factor=0.99, | |
| alpha=0.2, | |
| auto_alpha=True, | |
| lagrange_thresh=-1.0, | |
| min_q_weight=5.0, | |
| ), | |
| collect=dict( | |
| data_type='hdf5', | |
| data_path='./pendulum_sac_data_generation/expert_demos.hdf5', | |
| collector_logit=False, | |
| ), | |
| command=dict(), | |
| eval=dict(evaluator=dict(eval_freq=100, )), | |
| ), | |
| ) | |
| pendulum_cql_config = EasyDict(pendulum_cql_config) | |
| main_config = pendulum_cql_config | |
| pendulum_cql_create_config = dict( | |
| env=dict( | |
| type='pendulum', | |
| import_names=['dizoo.classic_control.pendulum.envs.pendulum_env'], | |
| ), | |
| env_manager=dict(type='base'), | |
| policy=dict( | |
| type='cql', | |
| import_names=['ding.policy.cql'], | |
| ), | |
| ) | |
| pendulum_cql_create_config = EasyDict(pendulum_cql_create_config) | |
| create_config = pendulum_cql_create_config | |
| if __name__ == "__main__": | |
| # or you can enter `ding -m serial_offline -c pendulum_cql_config.py -s 0` | |
| from ding.entry import serial_pipeline_offline | |
| serial_pipeline_offline([main_config, create_config], seed=0) | |