Merge branch 'develop' into fix/multioutput-bug

freqtrade/configuration/config_validation.py

@@ -355,6 +355,13 @@ def _validate_freqai_include_timeframes(conf: Dict[str, Any]) -> None:
                 f"Main timeframe of {main_tf} must be smaller or equal to FreqAI "
                 f"`include_timeframes`.Offending include-timeframes: {', '.join(offending_lines)}")
 
+        # Ensure that the base timeframe is included in the include_timeframes list
+        if main_tf not in freqai_include_timeframes:
+            feature_parameters = conf.get('freqai', {}).get('feature_parameters', {})
+            include_timeframes = [main_tf] + freqai_include_timeframes
+            conf.get('freqai', {}).get('feature_parameters', {}) \
+                .update({**feature_parameters, 'include_timeframes': include_timeframes})
+
 
 def _validate_freqai_backtest(conf: Dict[str, Any]) -> None:
     if conf.get('runmode', RunMode.OTHER) == RunMode.BACKTEST:

freqtrade/constants.py

@@ -608,9 +608,8 @@ CONF_SCHEMA = {
                 "backtest_period_days",
                 "identifier",
                 "feature_parameters",
-                "data_split_parameters",
-                "model_training_parameters"
-                ]
+                "data_split_parameters"
+            ]
         },
     },
 }

freqtrade/freqai/prediction_models/ReinforcementLearner.py

@@ -61,7 +61,7 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
             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['model_training_parameters']
+                                    **self.freqai_info.get('model_training_parameters', {})
                                     )
         else:
             logger.info('Continual training activated - starting training from previously '