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| from easydict import EasyDict | |
| phoenix_fqf_config = dict( | |
| exp_name='phoenix_fqf_seed0', | |
| env=dict( | |
| collector_env_num=8, | |
| evaluator_env_num=8, | |
| n_evaluator_episode=8, | |
| stop_value=10000000000, | |
| env_id='PhoenixNoFrameskip-v4', | |
| #'ALE/Phoenix-v5' is available. But special setting is needed after gym make. | |
| frame_stack=4, | |
| ), | |
| policy=dict( | |
| cuda=True, | |
| priority=False, | |
| model=dict( | |
| obs_shape=[4, 84, 84], | |
| action_shape=6, | |
| encoder_hidden_size_list=[128, 128, 512], | |
| num_quantiles=32, | |
| ), | |
| nstep=3, | |
| discount_factor=0.99, | |
| learn=dict( | |
| update_per_collect=10, | |
| batch_size=32, | |
| learning_rate_fraction=2.5e-9, | |
| learning_rate_quantile=0.00005, | |
| target_update_freq=500, | |
| ent_coef=0, | |
| ), | |
| collect=dict(n_sample=100, ), | |
| eval=dict(evaluator=dict(eval_freq=4000, )), | |
| other=dict( | |
| eps=dict( | |
| type='exp', | |
| start=1., | |
| end=0.05, | |
| decay=1000000, | |
| ), | |
| replay_buffer=dict(replay_buffer_size=1000000, ), | |
| ), | |
| ), | |
| ) | |
| phoenix_fqf_config = EasyDict(phoenix_fqf_config) | |
| main_config = phoenix_fqf_config | |
| phoenix_fqf_create_config = dict( | |
| env=dict( | |
| type='atari', | |
| import_names=['dizoo.atari.envs.atari_env'], | |
| ), | |
| env_manager=dict(type='subprocess'), | |
| policy=dict(type='fqf'), | |
| ) | |
| phoenix_fqf_create_config = EasyDict(phoenix_fqf_create_config) | |
| create_config = phoenix_fqf_create_config | |
| if __name__ == '__main__': | |
| # or you can enter `ding -m serial -c phoenix_fqf_config.py -s 0` | |
| from ding.entry import serial_pipeline | |
| serial_pipeline((main_config, create_config), seed=0) |