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| from easydict import EasyDict | |
| cartpole_discrete_dt_config = dict( | |
| exp_name='cartpole_dt_seed0', | |
| env=dict( | |
| collector_env_num=8, | |
| evaluator_env_num=5, | |
| n_evaluator_episode=5, | |
| stop_value=195, | |
| ), | |
| dataset=dict( | |
| data_dir_prefix='./cartpole_qrdqn_generation_data_seed0/expert_demos.hdf5', | |
| rtg_scale=None, | |
| context_len=20, | |
| env_type='classic', | |
| ), | |
| policy=dict( | |
| cuda=False, | |
| rtg_target=10, | |
| evaluator_env_num=5, | |
| clip_grad_norm_p=1.0, | |
| state_mean=1, | |
| state_std=0, | |
| model=dict( | |
| state_dim=4, | |
| act_dim=2, | |
| n_blocks=6, | |
| h_dim=128, | |
| context_len=20, | |
| n_heads=8, | |
| drop_p=0.1, | |
| continuous=False, | |
| ), | |
| max_timestep=1000, | |
| discount_factor=0.97, | |
| nstep=3, | |
| batch_size=64, | |
| learning_rate=0.001, | |
| target_update_freq=100, | |
| kappa=1.0, | |
| min_q_weight=4.0, | |
| collect=dict( | |
| data_type='hdf5', | |
| data_path='./cartpole_qrdqn_generation_data_seed0/expert_demos.hdf5', | |
| ), | |
| eval=dict(evaluator=dict(eval_freq=100, )), | |
| ), | |
| ) | |
| cartpole_discrete_dt_config = EasyDict(cartpole_discrete_dt_config) | |
| main_config = cartpole_discrete_dt_config | |
| cartpole_discrete_dt_create_config = dict( | |
| env=dict( | |
| type='cartpole', | |
| import_names=['dizoo.classic_control.cartpole.envs.cartpole_env'], | |
| ), | |
| env_manager=dict(type='base'), | |
| policy=dict(type='dt'), | |
| ) | |
| cartpole_discrete_dt_create_config = EasyDict(cartpole_discrete_dt_create_config) | |
| create_config = cartpole_discrete_dt_create_config | |
| # You can run this config with the entry file like `ding/example/dt.py` | |