add rl_config.device param to support use apple chip GPU

freqtrade/freqai/RL/BaseReinforcementLearningModel.py

@@ -44,6 +44,7 @@ class BaseReinforcementLearningModel(IFreqaiModel):
         self.max_threads = min(self.freqai_info['rl_config'].get(
             'cpu_count', 1), max(int(self.max_system_threads / 2), 1))
         th.set_num_threads(self.max_threads)
+        self.device = self.freqai_info['rl_config'].get('device', '')
         self.reward_params = self.freqai_info['rl_config']['model_reward_parameters']
         self.train_env: Union[SubprocVecEnv, Type[gym.Env]] = gym.Env()
         self.eval_env: Union[SubprocVecEnv, Type[gym.Env]] = gym.Env()

freqtrade/freqai/prediction_models/ReinforcementLearner.py

@@ -58,10 +58,16 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
                              net_arch=self.net_arch)
 
         if dk.pair not in self.dd.model_dictionary or not self.continual_learning:
+            kwargs = self.freqai_info.get('model_training_parameters', {})
+
+            # set device if device is not None
+            if self.device != '':
+                kwargs['device'] = self.device
+
             model = self.MODELCLASS(self.policy_type, self.train_env, policy_kwargs=policy_kwargs,
                                     tensorboard_log=Path(
                                         dk.full_path / "tensorboard" / dk.pair.split('/')[0]),
-                                    **self.freqai_info.get('model_training_parameters', {})
+                                    **kwargs
                                     )
         else:
             logger.info('Continual training activated - starting training from previously '