fix(qav3): ensure always the latest computed optuna HPs are used

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
index bfbcd5bb6afbec008fe64c9ddddabe1a8cc1105c..cced5a24a1c276bac23417a72f7108a13d858e42 100644 (file)
--- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
@@ -101,12 +101,14 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
             )
             if optuna_hp_params:
                 self.__optuna_hp_params[dk.pair] = optuna_hp_params
+            if optuna_hp_rmse:
+                self.__optuna_hp_rmse[dk.pair] = optuna_hp_rmse
+
+            if self.__optuna_hp_params.get(dk.pair):
                 model_training_parameters = {
                     **model_training_parameters,
                     **self.__optuna_hp_params[dk.pair],
                 }
-            if optuna_hp_rmse:
-                self.__optuna_hp_rmse[dk.pair] = optuna_hp_rmse
 
             optuna_period_params, optuna_period_rmse = self.optuna_period_optimize(
                 dk.pair,

diff --git a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
index 9312bdf4e58e87d211e1abfe5d57794fcc6137b2..be7ad108e01b90c7ff2cf2ec98b0cb0000d98144 100644 (file)
--- a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
@@ -101,12 +101,14 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
             )
             if optuna_hp_params:
                 self.__optuna_hp_params[dk.pair] = optuna_hp_params
+            if optuna_hp_rmse:
+                self.__optuna_hp_rmse[dk.pair] = optuna_hp_rmse
+
+            if self.__optuna_hp_params.get(dk.pair):
                 model_training_parameters = {
                     **model_training_parameters,
                     **self.__optuna_hp_params[dk.pair],
                 }
-            if optuna_hp_rmse:
-                self.__optuna_hp_rmse[dk.pair] = optuna_hp_rmse
 
             optuna_period_params, optuna_period_rmse = self.optuna_period_optimize(
                 dk.pair,