refactor(qav3): log time spent at optuna optimization

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 bed6fa8fc424434374b244764e89fac2ecb70eec..7c1644b05965e91456c473fb2bbb097746643161 100644 (file)
--- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
@@ -288,6 +288,7 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
             direction=optuna.study.StudyDirection.MINIMIZE,
             storage=storage,
         )
+        start = time.time()
         try:
             study.optimize(
                 lambda trial: hp_objective(
@@ -308,6 +309,8 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
         except Exception as e:
             logger.error(f"Optuna hp hyperopt failed: {e}", exc_info=True)
             return None
+        time_spent = time.time() - start
+        logger.info(f"Optuna hp hyperopt done ({time_spent:.2f} secs)")
 
         params = study.best_params
         # log params
@@ -343,6 +346,7 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
             direction=optuna.study.StudyDirection.MINIMIZE,
             storage=storage,
         )
+        start = time.time()
         try:
             study.optimize(
                 lambda trial: period_objective(
@@ -366,6 +370,8 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
         except Exception as e:
             logger.error(f"Optuna period hyperopt failed: {e}", exc_info=True)
             return None
+        time_spent = time.time() - start
+        logger.info(f"Optuna period hyperopt done ({time_spent:.2f} secs)")
 
         params = {"rmse": study.best_value, **study.best_params}
         # log params

diff --git a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
index 4933abc0f52caa2c1ec4f317776e038885e34085..301c469ed10738c2be8dd401dfec31cb8ed79e10 100644 (file)
--- a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
@@ -289,6 +289,7 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
             direction=optuna.study.StudyDirection.MINIMIZE,
             storage=storage,
         )
+        start = time.time()
         try:
             study.optimize(
                 lambda trial: hp_objective(
@@ -309,6 +310,8 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
         except Exception as e:
             logger.error(f"Optuna hp hyperopt failed: {e}", exc_info=True)
             return None
+        time_spent = time.time() - start
+        logger.info(f"Optuna hp hyperopt done ({time_spent:.2f} secs)")
 
         params = study.best_params
         # log params
@@ -344,6 +347,7 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
             direction=optuna.study.StudyDirection.MINIMIZE,
             storage=storage,
         )
+        start = time.time()
         try:
             study.optimize(
                 lambda trial: period_objective(
@@ -367,6 +371,8 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
         except Exception as e:
             logger.error(f"Optuna period hyperopt failed: {e}", exc_info=True)
             return None
+        time_spent = time.time() - start
+        logger.info(f"Optuna period hyperopt done ({time_spent:.2f} secs)")
 
         params = {"rmse": study.best_value, **study.best_params}
         # log params