clean RL tests to avoid dir pollution and increase speed
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@@ -24,7 +24,7 @@ class ReinforcementLearner_test_4ac(BaseReinforcementLearningModel):
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total_timesteps = self.freqai_info["rl_config"]["train_cycles"] * len(train_df)
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policy_kwargs = dict(activation_fn=th.nn.ReLU,
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net_arch=[128, 128])
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net_arch=[64, 64])
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if dk.pair not in self.dd.model_dictionary or not self.continual_learning:
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model = self.MODELCLASS(self.policy_type, self.train_env, policy_kwargs=policy_kwargs,
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