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from easydict import EasyDict |
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pendulum_cql_config = dict( |
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exp_name='pendulum_cql', |
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env=dict( |
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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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stop_value=-250, |
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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=3, |
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action_shape=1, |
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twin_critic=True, |
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action_space='reparameterization', |
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actor_head_hidden_size=128, |
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critic_head_hidden_size=128, |
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), |
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learn=dict( |
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train_epoch=30000, |
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batch_size=128, |
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learning_rate_q=3e-4, |
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learning_rate_policy=1e-3, |
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learning_rate_alpha=1e-3, |
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ignore_done=True, |
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target_theta=0.005, |
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discount_factor=0.99, |
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alpha=0.2, |
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auto_alpha=True, |
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lagrange_thresh=-1.0, |
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min_q_weight=5.0, |
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), |
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collect=dict( |
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data_type='hdf5', |
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data_path='./pendulum_sac_data_generation/expert_demos.hdf5', |
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collector_logit=False, |
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), |
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command=dict(), |
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eval=dict(evaluator=dict(eval_freq=100, )), |
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), |
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) |
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pendulum_cql_config = EasyDict(pendulum_cql_config) |
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main_config = pendulum_cql_config |
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pendulum_cql_create_config = dict( |
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env=dict( |
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type='pendulum', |
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import_names=['dizoo.classic_control.pendulum.envs.pendulum_env'], |
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), |
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env_manager=dict(type='base'), |
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policy=dict( |
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type='cql', |
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import_names=['ding.policy.cql'], |
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), |
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) |
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pendulum_cql_create_config = EasyDict(pendulum_cql_create_config) |
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create_config = pendulum_cql_create_config |
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if __name__ == "__main__": |
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from ding.entry import serial_pipeline_offline |
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serial_pipeline_offline([main_config, create_config], seed=0) |
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