PPO policy change + verbose=1
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@ -53,8 +53,8 @@ class ReinforcementLearningPPO(BaseReinforcementLearningModel):
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policy_kwargs = dict(activation_fn=th.nn.ReLU,
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policy_kwargs = dict(activation_fn=th.nn.ReLU,
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net_arch=[256, 256, 128])
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net_arch=[256, 256, 128])
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model = PPO('MultiInputPolicy', train_env, policy_kwargs=policy_kwargs,
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model = PPO('MlpPolicy', train_env, policy_kwargs=policy_kwargs,
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tensorboard_log=f"{path}/ppo/tensorboard/", learning_rate=0.00025, gamma=0.9
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tensorboard_log=f"{path}/ppo/tensorboard/", learning_rate=0.00025, gamma=0.9, verbose=1
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)
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)
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model.learn(
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model.learn(
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