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| from easydict import EasyDict | |
| walker2d_gcl_config = dict( | |
| exp_name='walker2d_gcl_seed0', | |
| env=dict( | |
| env_id='Walker2d-v3', | |
| norm_obs=dict(use_norm=False, ), | |
| norm_reward=dict(use_norm=False, ), | |
| collector_env_num=8, | |
| evaluator_env_num=10, | |
| n_evaluator_episode=10, | |
| stop_value=3000, | |
| ), | |
| reward_model=dict( | |
| learning_rate=0.001, | |
| input_size=23, | |
| batch_size=32, | |
| action_shape=6, | |
| continuous=True, | |
| update_per_collect=20, | |
| ), | |
| policy=dict( | |
| cuda=False, | |
| recompute_adv=True, | |
| action_space='continuous', | |
| model=dict( | |
| obs_shape=17, | |
| action_shape=6, | |
| action_space='continuous', | |
| ), | |
| learn=dict( | |
| update_per_collect=10, | |
| batch_size=64, | |
| learning_rate=3e-4, | |
| value_weight=0.5, | |
| entropy_weight=0.0, | |
| clip_ratio=0.2, | |
| adv_norm=True, | |
| ), | |
| collect=dict( | |
| # Users should add their own model path here. Model path should lead to a model. | |
| # Absolute path is recommended. | |
| # In DI-engine, it is ``exp_name/ckpt/ckpt_best.pth.tar``. | |
| model_path='model_path_placeholder', | |
| # If you need the data collected by the collector to contain logit key which reflect the probability of | |
| # the action, you can change the key to be True. | |
| # In Guided cost Learning, we need to use logit to train the reward model, we change the key to be True. | |
| collector_logit=True, | |
| n_sample=2048, | |
| unroll_len=1, | |
| discount_factor=0.99, | |
| gae_lambda=0.97, | |
| ), | |
| eval=dict(evaluator=dict(eval_freq=100, )), | |
| ), | |
| ) | |
| walker2d_gcl_config = EasyDict(walker2d_gcl_config) | |
| main_config = walker2d_gcl_config | |
| walker2d_gcl_create_config = dict( | |
| env=dict( | |
| type='mujoco', | |
| import_names=['dizoo.mujoco.envs.mujoco_env'], | |
| ), | |
| env_manager=dict(type='subprocess'), | |
| policy=dict(type='ppo', ), | |
| replay_buffer=dict(type='naive', ), | |
| reward_model=dict(type='guided_cost'), | |
| ) | |
| walker2d_gcl_create_config = EasyDict(walker2d_gcl_create_config) | |
| create_config = walker2d_gcl_create_config | |
| if __name__ == '__main__': | |
| from ding.entry import serial_pipeline_guided_cost | |
| serial_pipeline_guided_cost((main_config, create_config), seed=0) | |