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from easydict import EasyDict |
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pendulum_d4pg_config = dict( |
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exp_name='pendulum_d4pg_seed0', |
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env=dict( |
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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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stop_value=-250, |
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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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nstep=3, |
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discount_factor=0.995, |
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random_collect_size=800, |
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model=dict( |
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obs_shape=3, |
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action_shape=1, |
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action_space='regression', |
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v_min=-100, |
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v_max=100, |
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n_atom=51, |
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), |
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learn=dict( |
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update_per_collect=2, |
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batch_size=128, |
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learning_rate_actor=0.001, |
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learning_rate_critic=0.001, |
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ignore_done=True, |
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actor_update_freq=1, |
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noise=False, |
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), |
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collect=dict( |
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n_sample=48, |
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noise_sigma=0.1, |
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collector=dict(collect_print_freq=1000, ), |
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), |
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eval=dict(evaluator=dict(eval_freq=100, ), ), |
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other=dict(replay_buffer=dict( |
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replay_buffer_size=20000, |
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max_use=16, |
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), ), |
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), |
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) |
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pendulum_d4pg_config = EasyDict(pendulum_d4pg_config) |
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main_config = pendulum_d4pg_config |
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pendulum_d4pg_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(type='d4pg'), |
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) |
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pendulum_d4pg_create_config = EasyDict(pendulum_d4pg_create_config) |
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create_config = pendulum_d4pg_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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