Open Abhranta opened 2 years ago
Since params are stored in database you can get the best using this method:
import logging
import optuna
import os
from typing import Optional
logger = logging.getLogger(__name__)
def get_best_params(output: str) -> Optional[dict]:
"""
Args:
output (str): the output directory given to Autoxgb
Returns:
Optional[dict]: best params if exist else None
"""
params_path = os.path.join(output, "params.db")
if not os.path.exists(params_path):
logger.error(f"params doesn't exist. Invalid path: {params_path}")
return None
best_params: Optional[dict] = None
try:
study = optuna.load_study(study_name="autoxgb", storage=f"sqlite:///{params_path}")
except Exception as exc:
logger.error("Error while loading optuna study from database", exc_info=exc)
else:
best_params = study.best_params
finally:
return best_params
Hi, I want to see the parameters of the trained model after the training is complete. Can anyone help me out with it ?