Directly set model_type in base RL model
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@ -64,6 +64,7 @@ class BaseReinforcementLearningModel(IFreqaiModel):
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self.policy_type = self.freqai_info['rl_config']['policy_type']
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self.unset_outlier_removal()
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self.net_arch = self.rl_config.get('net_arch', [128, 128])
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self.dd.model_type = "stable_baselines"
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def unset_outlier_removal(self):
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"""
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@ -99,11 +99,6 @@ class FreqaiDataDrawer:
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self.empty_pair_dict: pair_info = {
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"model_filename": "", "trained_timestamp": 0,
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"data_path": "", "extras": {}}
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if 'Reinforcement' in self.config['freqaimodel']:
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self.model_type = 'stable_baselines'
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logger.warning('User passed a ReinforcementLearner model, FreqAI will '
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'now use stable_baselines3 to save models.')
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else:
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self.model_type = self.freqai_info.get('model_save_type', 'joblib')
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def update_metric_tracker(self, metric: str, value: float, pair: str) -> None:
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