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from easydict import EasyDict |
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bipedalwalker_td3_config = dict( |
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exp_name='bipedalwalker_td3_seed0', |
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env=dict( |
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env_id='BipedalWalker-v3', |
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collector_env_num=8, |
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evaluator_env_num=5, |
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act_scale=True, |
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n_evaluator_episode=5, |
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rew_clip=True, |
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), |
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policy=dict( |
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cuda=True, |
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random_collect_size=10000, |
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model=dict( |
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obs_shape=24, |
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action_shape=4, |
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twin_critic=True, |
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action_space='regression', |
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actor_head_hidden_size=400, |
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critic_head_hidden_size=400, |
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), |
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learn=dict( |
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update_per_collect=64, |
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batch_size=256, |
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learning_rate_actor=0.0003, |
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learning_rate_critic=0.0003, |
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target_theta=0.005, |
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discount_factor=0.99, |
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actor_update_freq=2, |
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noise=True, |
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noise_sigma=0.2, |
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noise_range=dict( |
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min=-0.5, |
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max=0.5, |
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), |
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learner=dict(hook=dict(log_show_after_iter=1000, )) |
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), |
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collect=dict(n_sample=64, ), |
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other=dict(replay_buffer=dict(replay_buffer_size=300000, ), ), |
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), |
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) |
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bipedalwalker_td3_config = EasyDict(bipedalwalker_td3_config) |
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main_config = bipedalwalker_td3_config |
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bipedalwalker_td3_create_config = dict( |
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env=dict( |
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type='bipedalwalker', |
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import_names=['dizoo.box2d.bipedalwalker.envs.bipedalwalker_env'], |
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), |
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env_manager=dict(type='subprocess'), |
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policy=dict(type='td3'), |
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) |
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bipedalwalker_td3_create_config = EasyDict(bipedalwalker_td3_create_config) |
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create_config = bipedalwalker_td3_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, max_env_step=int(1e5)) |
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