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| from easydict import EasyDict | |
| import torch | |
| from copy import deepcopy | |
| lunarlander_dt_config = dict( | |
| exp_name='data_dt/lunarlander_dt_1000eps_rtgt300_meel1000_seed0_debug', | |
| env=dict( | |
| env_id='LunarLander-v2', | |
| evaluator_env_num=8, | |
| n_evaluator_episode=8, | |
| stop_value=200, | |
| ), | |
| policy=dict( | |
| stop_value=200, | |
| state_mean=None, | |
| state_std=None, | |
| device='cuda', | |
| env_name='LunarLander-v2', | |
| rtg_target=300, # max target reward_to_go | |
| rtg_scale=150, | |
| max_eval_ep_len=1000, # max len of one episode # TODO | |
| wt_decay=1e-4, | |
| warmup_steps=10000, | |
| context_len=20, # TODO | |
| evaluator_env_num=8, | |
| log_dir='DI-engine/dizoo/box2d/lunarlander/dt_log_1000eps', | |
| model=dict( | |
| state_dim=8, | |
| act_dim=4, | |
| n_blocks=3, | |
| h_dim=128, | |
| context_len=20, | |
| n_heads=1, | |
| drop_p=0.1, | |
| continuous=False, # TODO | |
| ), | |
| discount_factor=0.999, | |
| nstep=3, | |
| learn=dict( | |
| dataset_path='DI-engine/dizoo/box2d/lunarlander/offline_data/dt_data/dqn_data_1000eps.pkl', # TODO | |
| learning_rate=3e-4, | |
| batch_size=64, # training batch size | |
| target_update_freq=100, | |
| ), | |
| collect=dict( | |
| data_type='d4rl_trajectory', | |
| data_path='DI-engine/dizoo/box2d/lunarlander/offline_data/dt_data/dqn_data_1000eps.pkl', | |
| unroll_len=1, | |
| ), | |
| eval=dict(evaluator=dict(eval_freq=100, )), | |
| ), | |
| ) | |
| lunarlander_dt_config = EasyDict(lunarlander_dt_config) | |
| main_config = lunarlander_dt_config | |
| lunarlander_dt_create_config = dict( | |
| env=dict( | |
| type='lunarlander', | |
| import_names=['dizoo.box2d.lunarlander.envs.lunarlander_env'], | |
| ), | |
| env_manager=dict(type='subprocess'), | |
| policy=dict(type='dt'), | |
| ) | |
| lunarlander_dt_create_config = EasyDict(lunarlander_dt_create_config) | |
| create_config = lunarlander_dt_create_config | |