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from easydict import EasyDict |
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main_config = dict( |
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exp_name='hopper_expert_td3-bc_seed0', |
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env=dict( |
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env_id='hopper-expert-v2', |
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collector_env_num=1, |
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evaluator_env_num=8, |
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use_act_scale=True, |
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n_evaluator_episode=8, |
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stop_value=6000, |
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), |
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policy=dict( |
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cuda=True, |
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model=dict( |
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obs_shape=11, |
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action_shape=3, |
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), |
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learn=dict( |
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train_epoch=30000, |
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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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actor_update_freq=2, |
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noise=True, |
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noise_sigma=0.2, |
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noise_range={ |
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'min': -0.5, |
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'max': 0.5 |
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}, |
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alpha=2.5, |
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), |
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collect=dict( |
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data_type='d4rl', |
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data_path=None, |
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), |
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eval=dict(evaluator=dict(eval_freq=10000, )), |
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other=dict(replay_buffer=dict(replay_buffer_size=2000000, ), ), |
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), |
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) |
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main_config = EasyDict(main_config) |
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main_config = main_config |
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create_config = dict( |
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env=dict( |
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type='d4rl', |
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import_names=['dizoo.d4rl.envs.d4rl_env'], |
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), |
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env_manager=dict( |
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cfg_type='BaseEnvManagerDict', |
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type='base', |
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), |
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policy=dict( |
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type='td3_bc', |
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import_names=['ding.policy.td3_bc'], |
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), |
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replay_buffer=dict(type='naive', ), |
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) |
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create_config = EasyDict(create_config) |
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create_config = create_config |
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