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from easydict import EasyDict |
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pendulum_ppo_config = dict( |
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exp_name='pendulum_ppo_seed0', |
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env=dict( |
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collector_env_num=10, |
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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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action_space='continuous', |
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recompute_adv=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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encoder_hidden_size_list=[64, 64], |
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action_space='continuous', |
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actor_head_layer_num=0, |
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critic_head_layer_num=0, |
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sigma_type='conditioned', |
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bound_type='tanh', |
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), |
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learn=dict( |
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epoch_per_collect=10, |
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batch_size=32, |
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learning_rate=3e-5, |
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value_weight=0.5, |
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entropy_weight=0.0, |
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clip_ratio=0.2, |
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adv_norm=False, |
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value_norm=True, |
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ignore_done=True, |
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), |
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collect=dict( |
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n_sample=200, |
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unroll_len=1, |
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discount_factor=0.9, |
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gae_lambda=1., |
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), |
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eval=dict(evaluator=dict(eval_freq=200, )) |
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), |
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) |
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pendulum_ppo_config = EasyDict(pendulum_ppo_config) |
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main_config = pendulum_ppo_config |
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pendulum_ppo_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='ppo'), |
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) |
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pendulum_ppo_create_config = EasyDict(pendulum_ppo_create_config) |
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create_config = pendulum_ppo_create_config |
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if __name__ == "__main__": |
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from ding.entry import serial_pipeline_onpolicy |
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serial_pipeline_onpolicy([main_config, create_config], seed=0) |
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