added logging to Tuner

luxonis_train/core/tuner.py

@@ -1,5 +1,6 @@
 import os.path as osp
 from typing import Any
+from logging import getLogger
 
 import lightning.pytorch as pl
 import optuna
@@ -13,6 +14,8 @@
 
 from .core import Core
 
+logger = getLogger(__name__)
+
 
 class Tuner(Core):
     def __init__(self, cfg: str | dict, args: list[str] | tuple[str, ...] | None):
@@ -32,6 +35,7 @@ def __init__(self, cfg: str | dict, args: list[str] | tuple[str, ...] | None):
 
     def tune(self) -> None:
         """Runs Optuna tunning of hyperparameters."""
+        logger.info("Starting tuning...")
 
         pruner = (
             optuna.pruners.MedianPruner()
@@ -66,6 +70,8 @@ def tune(self) -> None:
             timeout=self.tune_cfg.timeout,
         )
 
+        logger.info(f"Best study parameters: {study.best_params}")
+
     def _objective(self, trial: optuna.trial.Trial) -> float:
         """Objective function used to optimize Optuna study."""
         rank = rank_zero_only.rank