fix(qav3): ensure previous optuna params are reused in case of failure

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 f4b0d46e68a60e0541d89056eeaca4517706f4c5..c14e396720cf19dc53b0bf564fe9f47516cd56d6 100644 (file)
--- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
@@ -81,7 +81,7 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
                 if dk.pair not in self.__optuna_hp:
                     self.__optuna_hp[dk.pair] = {}
                 self.__optuna_hp[dk.pair] = params
-
+            if self.__optuna_hp.get(dk.pair):
                 train_window = self.__optuna_hp[dk.pair].get("train_period_candles")
                 X = X.tail(train_window)
                 y = y.tail(train_window)
@@ -287,7 +287,7 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
             )
         except Exception as e:
             logger.error(
-                f"Optuna hyperopt failed: {e}. Please consider using a concurrency friendly storage backend like 'file' or lower the number of jobs."
+                f"Optuna hyperopt failed: {e}. Consider using a concurrency friendly storage backend like 'file' or lower the number of jobs."
             )
             hyperopt_failed = True
 

diff --git a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
index ce0b8a952b84b3b224804db6b6d97fb892625858..3c6cb575a0f4e2e170c018c971948eb184bfbb77 100644 (file)
--- a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
@@ -85,7 +85,7 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
                 if dk.pair not in self.__optuna_hp:
                     self.__optuna_hp[dk.pair] = {}
                 self.__optuna_hp[dk.pair] = params
-
+            if self.__optuna_hp.get(dk.pair):
                 train_window = self.__optuna_hp[dk.pair].get("train_period_candles")
                 X = X.tail(train_window)
                 y = y.tail(train_window)
@@ -290,7 +290,7 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
             )
         except Exception as e:
             logger.error(
-                f"Optuna hyperopt failed: {e}. Please consider using a concurrency friendly storage backend like 'file' or lower the number of jobs."
+                f"Optuna hyperopt failed: {e}. Consider using a concurrency friendly storage backend like 'file' or lower the number of jobs."
             )
             hyperopt_failed = True