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from easydict import EasyDict |
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gym_hybrid_hppo_config = dict( |
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exp_name='gym_hybrid_hppo_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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env_id='Moving-v0', |
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n_evaluator_episode=5, |
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stop_value=1.8, |
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), |
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policy=dict( |
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cuda=True, |
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action_space='hybrid', |
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recompute_adv=True, |
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model=dict( |
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obs_shape=10, |
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action_shape=dict( |
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action_type_shape=3, |
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action_args_shape=2, |
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), |
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action_space='hybrid', |
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encoder_hidden_size_list=[256, 128, 64, 64], |
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sigma_type='fixed', |
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fixed_sigma_value=0.3, |
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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=320, |
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learning_rate=3e-4, |
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entropy_weight=0.5, |
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adv_norm=True, |
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value_norm=True, |
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), |
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collect=dict( |
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n_sample=3200, |
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discount_factor=0.99, |
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gae_lambda=0.95, |
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collector=dict(collect_print_freq=1000, ), |
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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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gym_hybrid_hppo_config = EasyDict(gym_hybrid_hppo_config) |
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main_config = gym_hybrid_hppo_config |
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gym_hybrid_hppo_create_config = dict( |
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env=dict( |
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type='gym_hybrid', |
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import_names=['dizoo.gym_hybrid.envs.gym_hybrid_env'], |
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), |
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env_manager=dict(type='subprocess'), |
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policy=dict(type='ppo'), |
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) |
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gym_hybrid_hppo_create_config = EasyDict(gym_hybrid_hppo_create_config) |
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create_config = gym_hybrid_hppo_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, max_env_step=int(1e7)) |
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