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from easydict import EasyDict |
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nstep = 3 |
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lunarlander_dqn_config = dict( |
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exp_name='lunarlander_dqn_deque_seed0', |
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env=dict( |
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collector_env_num=8, |
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evaluator_env_num=8, |
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env_id='LunarLander-v2', |
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n_evaluator_episode=8, |
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stop_value=200, |
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), |
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policy=dict( |
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cuda=False, |
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priority=True, |
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priority_IS_weight=False, |
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model=dict( |
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obs_shape=8, |
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action_shape=4, |
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encoder_hidden_size_list=[512, 64], |
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dueling=True, |
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), |
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discount_factor=0.99, |
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nstep=nstep, |
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learn=dict( |
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update_per_collect=10, |
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batch_size=64, |
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learning_rate=0.001, |
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target_update_freq=100, |
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), |
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collect=dict( |
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n_sample=64, |
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unroll_len=1, |
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), |
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other=dict( |
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eps=dict( |
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type='exp', |
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start=0.95, |
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end=0.1, |
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decay=50000, |
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), |
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replay_buffer=dict(replay_buffer_size=100000, ) |
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), |
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), |
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) |
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lunarlander_dqn_config = EasyDict(lunarlander_dqn_config) |
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main_config = lunarlander_dqn_config |
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lunarlander_dqn_create_config = dict( |
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env=dict( |
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type='lunarlander', |
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import_names=['dizoo.box2d.lunarlander.envs.lunarlander_env'], |
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), |
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env_manager=dict(type='subprocess'), |
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policy=dict(type='dqn'), |
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replay_buffer=dict(type='deque'), |
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) |
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lunarlander_dqn_create_config = EasyDict(lunarlander_dqn_create_config) |
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create_config = lunarlander_dqn_create_config |
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if __name__ == "__main__": |
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from ding.entry import serial_pipeline |
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serial_pipeline([main_config, create_config], seed=0) |
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