Spaces:
Sleeping
Sleeping
| from easydict import EasyDict | |
| cliffwalking_dqn_config = dict( | |
| exp_name='cliffwalking_dqn_seed0', | |
| env=dict( | |
| collector_env_num=8, | |
| evaluator_env_num=8, | |
| n_evaluator_episode=8, | |
| stop_value=-13, # the optimal value of cliffwalking env | |
| max_episode_steps=300, | |
| ), | |
| policy=dict( | |
| cuda=True, | |
| load_path="./cliffwalking_dqn_seed0/ckpt/ckpt_best.pth.tar", | |
| model=dict( | |
| obs_shape=48, | |
| action_shape=4, | |
| encoder_hidden_size_list=[512, 64], | |
| ), | |
| discount_factor=0.99, | |
| nstep=1, | |
| learn=dict( | |
| update_per_collect=10, | |
| batch_size=128, | |
| learning_rate=0.001, | |
| target_update_freq=100, | |
| ), | |
| collect=dict( | |
| n_sample=64, | |
| unroll_len=1, | |
| ), | |
| other=dict( | |
| eps=dict( | |
| type='linear', | |
| start=0.95, | |
| end=0.25, | |
| decay=50000, | |
| ), | |
| replay_buffer=dict(replay_buffer_size=100000, ) | |
| ), | |
| ), | |
| ) | |
| cliffwalking_dqn_config = EasyDict(cliffwalking_dqn_config) | |
| main_config = cliffwalking_dqn_config | |
| cliffwalking_dqn_create_config = dict( | |
| env=dict( | |
| type='cliffwalking', | |
| import_names=['dizoo.cliffwalking.envs.cliffwalking_env'], | |
| ), | |
| env_manager=dict(type='subprocess'), | |
| policy=dict(type='dqn'), | |
| ) | |
| cliffwalking_dqn_create_config = EasyDict(cliffwalking_dqn_create_config) | |
| create_config = cliffwalking_dqn_create_config | |
| if __name__ == "__main__": | |
| # or you can enter `ding -m serial -c cliffwalking_dqn_config.py -s 0` | |
| from ding.entry import serial_pipeline | |
| serial_pipeline([main_config, create_config], seed=0) | |